Sensory control device, sensory control method, sensory control system

Abstract

To provide a technology that provides sensory feedback in accordance with the physical characteristics of the control unit. [Solution] The present invention comprises an operating unit, an operating detection unit that detects operation of the operating unit and generates an operating signal, a signal generation unit that generates a sensory presentation signal based on the operating signal, and a sensory presentation unit that provides sensory presentation to the operator based on the sensory presentation signal, and an adjustment unit that adjusts at least one of the operating signal, sensory presentation signal, and sensory presentation when operating the operating unit, based on the mass and size of the operating unit as physical characteristics, wherein the operating unit is a rotary operating unit, and the adjustment unit adjusts at least one of the operating signal, sensory presentation signal, and sensory presentation when operating the rotary operating unit as physical characteristics, based on the mass and radius, diameter, or length of the maximum part of the operating unit as physical characteristics.

Description

[Technical Field]

[0001] The present invention relates to a sensory control device, a sensory control method, and a sensory control system. [Background technology]

[0002] Conventionally, control units that provide sensory feedback by stimulating a person are known. Here, sensory feedback includes tactile feedback, auditory feedback through sound, and visual feedback through image display, etc. Sensory feedback is adjusted by adjusting the signals that drive various control units.

[0003] Game controllers with interchangeable buttons and other components that incorporate vibration devices are known (see, for example, Patent Document 3). Patent Document 3 discloses a technique for replacing the vibration device itself to achieve different vibration intensities. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2019-220168 [Patent Document 2] Patent No. 5662425 [Patent Document 3] Special Publication No. 2020-523068 [Patent Document 4] Special Publication No. 2013-519961 [Overview of the project] [Problems that the invention aims to solve]

[0005] However, conventional technology has a problem in that it does not adequately provide sensory feedback that corresponds to the physical characteristics of the control unit. For example, in the case of a rotary control unit, the size and mass of the control unit can affect the sensation transmitted to the user operating the unit, even if the actuator is driven in the same way.

[0006] In view of the above problems, the present invention aims to provide a technology for providing sensory feedback in accordance with the physical characteristics of the operating part. [Means for solving the problem]

[0007] In view of the above problems, the present invention provides a sensory control device comprising: an operating unit; an operating detection unit that detects operation of the operating unit and generates an operating signal; a signal generation unit that generates a sensory presentation signal based on the operating signal; and a sensory presentation unit that provides sensory presentation to the operator based on the sensory presentation signal, wherein the operating unit is a rotary operating unit, and the operating unit is a rotary operating unit signal, and the sensory presentation signal, and the operating unit, and the operating signal, and the operating signal, and the operating signal, and the operating signal, and the operating signal,

[0008] In view of the above problems, the present invention provides a sensory control device comprising: an operating unit; an operating detection unit that detects operation of the operating unit and generates an operating signal; a signal generation unit that generates a sensory presentation signal based on the operating signal; and a sensory presentation unit that provides sensory presentation to the operator based on the sensory presentation signal, wherein the operating unit is a press-type operating unit, and the operating unit is a press-type operating unit detection unit is a press-type operating unit, and the operating detection unit is a press-type operating unit, and the operating detection unit is a press-type operating unit, and the operating detection unit is a press-type operating unit, and the operating detection unit is a press-type operating unit, and the operating detection unit is a

[0009] In view of the above problems, the present invention includes an operation unit, an operation detection unit that detects an operation of the operation unit and generates an operation signal, a signal generation unit that generates a sensory presentation signal based on the operation signal, and a sensory presentation unit that performs sensory presentation to an operator based on the sensory presentation signal. The present invention further includes an adjustment unit that uses the mass and size of the operation unit as physical characteristics and adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation when operating the operation unit based on the mass and size. The operation unit is a slide operation unit. The present invention uses the mass of the operation unit and any one of the slide amount, height, width, and thickness as physical characteristics and adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation when sliding the slide operation unit based on the mass and any one of the slide amount, height, width, and thickness. The present invention provides a sensory control device characterized by the above.

[0010] In view of the above problems, the present invention includes an operation unit, an operation detection unit that detects an operation of the operation unit and generates an operation signal, a signal generation unit that generates a sensory presentation signal based on the operation signal, and a sensory presentation unit that performs sensory presentation to an operator based on the sensory presentation signal. The present invention further includes an adjustment unit that uses the mass and size of the operation unit as physical characteristics and adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation when operating the operation unit based on the mass and size. The operation unit is a pivot operation unit. The present invention uses the mass of the operation unit and the length of the operation unit as physical characteristics and adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation when tilting the pivot operation unit based on the mass and the length of the operation unit. The present invention provides a sensory control device characterized by the above.

Effects of the Invention

[0011] It is possible to provide a technique for performing sensory presentation according to the physical characteristics of the operation unit.

Brief Description of the Drawings

[0012] [Figure 1] It is a block diagram showing a basic configuration of a sensory control system according to an embodiment of the present disclosure. [Figure 2] This is a block diagram showing a tactile control system as a first embodiment of the sensory control system relating to this disclosure. [Figure 3] Figure 2 is an explanatory diagram illustrating an example of the configuration of the haptic presentation unit included in the haptic control system, using an equivalent circuit with Laplace transform operators. [Figure 4] Figure 2 is an explanatory diagram showing an equivalent model of an example of a haptic presentation unit included in the haptic control system. [Figure 5] Figure 4 is an explanatory diagram illustrating the equivalent circuit and internal structure of an example actuator. [Figure 6] This is a flowchart illustrating a method for generating a transformation model using the transformation model generation system disclosed herein. [Figure 7] This flowchart illustrates specific examples of the transformation model generation method and haptic presentation method described herein. [Figure 8] This is a flowchart illustrating a haptic control method using the haptic control system of this disclosure. [Figure 9] This is an explanatory diagram of the physical properties of a pressure-type operating tool. [Figure 10] This is an explanatory diagram showing an example of the physical parameters of a pressure-type operating tool. [Figure 11] This is an explanatory diagram of the operation of a pressure-type operating tool. [Figure 12] This is an explanatory diagram showing the relationship between sensory parameters and physical parameters in a pressure-type operating device. [Figure 13] This is an explanatory diagram showing the relationship between sensory parameters and physical parameters in a pressure-type operating device. [Figure 14] This is an explanatory diagram showing the relationship between sensory parameters and physical parameters in a pressure-type operating device. [Figure 15] This is an explanatory diagram showing the relationship between sensory parameters and physical parameters in a pressure-type operating device. [Figure 16] This is an explanatory diagram of the physical properties of a pressure-type operating tool. [Figure 17] This is an explanatory diagram illustrating the relationship between sensory parameters and physical parameters in a rotary-type operating device. [Figure 18] This is an explanatory diagram of the physical properties of a rotary-type operating tool. [Figure 19] This is a block diagram showing the configuration of a rotary-operated device. [Figure 20] This is a block diagram showing a tactile control system as a second embodiment of a sensory control system according to one embodiment of the present disclosure. [Figure 21] Figure 20 is a sequence diagram showing the operation of the haptic control system. [Figure 22] This figure shows the first relational expression relating to an example of the transformation model generation method of this disclosure. [Figure 23] This figure shows the second relational expression relating to an example of the transformation model generation method of this disclosure. [Figure 24] This figure shows an example of the time variation in the intensity of the drive signal supplied to the weight based on tactile feedback signals. [Figure 25] This is an example of a perspective view of a tactile control device. [Figure 26] This is an example of a client-server type haptic control system. [Figure 27] This is an example of a diagram illustrating the process of a user adjusting the feel of an operation using a tactile control device. [Figure 28] This is an example of a diagram illustrating the process of a user adjusting the feel of an operation using a tactile control device. [Figure 29] This is an example of a functional block diagram illustrating the functions of a tactile control device. [Figure 30] This is an example of a flowchart illustrating the learning process in the generation of the classification unit. [Figure 31] This flowchart illustrates the learning process for the correspondence between the expressiveness of affective parameters and physical parameters. [Figure 32] This is an example of a flowchart illustrating how a haptic control device uses a classification unit and first to third transformation models to present the user with preferred tactile sensations. [Figure 33] This diagram illustrates the process of a user adjusting the feel of an operation using a tactile control device. [Figure 34]This is an example of a functional block diagram illustrating the functions of a tactile control device. [Figure 35] This is an example of a flowchart illustrating the learning process for physical parameters (load-displacement curves) corresponding to the representation frequency. [Figure 36] This is an example of a flowchart illustrating the process of curve fitting the load-displacement curve of a standard operating device. [Figure 37] This is an example of a flowchart illustrating how a haptic control device uses a physical parameter conversion unit and a comparison unit to present the user with a preferred tactile sensation. [Figure 38] This figure shows an example of a neural network when the classification unit is implemented using a neural network. [Figure 39] This figure shows an example of a decision tree where the classification unit is implemented using a decision tree. [Figure 40] This diagram explains the first input screen for the expression frequency. [Figure 41] This is an example of a functional block diagram of a haptic control system in which the first form of haptic control device is applied to a client-server system. [Figure 42] This is an example of a sequence diagram illustrating the operation of a haptic control system. [Figure 43] This is an example of a functional block diagram of a haptic control system in which a second form of haptic control device is applied to a client-server system. [Figure 44] This is an example of a sequence diagram illustrating the operation of the second form of haptic control system. [Figure 45] This figure shows the configuration of the tactile control system within the sensory control system (Example 2). [Figure 46] This figure shows an example of the control panel parameters. [Figure 47] This diagram illustrates the differences in the physical characteristics of the control unit. [Figure 48] This diagram illustrates several methods for detecting the size and mass of an operating unit using an operating unit sensor. [Figure 49] This diagram illustrates the method for estimating the mass of the operating part through calibration. [Figure 50] This diagram illustrates the correction of the mass of the operating section. [Figure 51] This flowchart illustrates the process of adjusting tactile feedback signals according to the physical parameters of the control unit to which the tactile control system is installed. [Figure 52] This flowchart (modified) illustrates the process of adjusting haptic feedback signals according to the physical parameters of the control unit to which the haptic control system is attached. [Figure 53] Figure 45 shows the configuration of a tactile control system as a second embodiment of the sensory control system shown, along with the signal flow. [Figure 54] This is a sequence diagram showing how a communication device and a terminal device communicate to estimate the sensory parameters of an attached control unit. [Figure 55] This diagram illustrates the static properties obtained by a rigid pressing tool and the dynamic properties obtained by a finger model pressing tool that integrates a rigid body and an elastic body. [Figure 56] This diagram illustrates the relative position of the finger and the tool when the finger deforms. [Figure 57] This is a diagram illustrating a finger model pressure device. [Figure 58] This diagram illustrates the generation of sensory signals that convey a click sensation. [Figure 59] This is an example of a functional configuration diagram and block diagram for a pressure-type operating device. [Figure 60] This diagram illustrates the dynamic characteristics when a control device is pressed using a finger model press. [Figure 61] This diagram illustrates the temporal transition of the relative positions of the finger model presser and the operating tool. [Figure 62] This diagram provides a more detailed explanation of the dynamic characteristics along with periods A through C. [Figure 63] This is an example of a diagram showing the dynamic characteristics when multiple operating tools with different dynamic characteristics are pressed using a finger model press tool. [Figure 64] This is an example of a flowchart illustrating the process of determining physical parameters that correlate with emotional parameters. [Figure 65]This is a scatter plot of the dynamic characteristics and expressiveness levels of each control device for the "feeling of recovery (or lack thereof)" sensory parameter acquired by the processor in step ST153. [Figure 66] This is a scatter plot of the dynamic characteristics and expressiveness levels of each control device for the "feeling of being drawn in (or not being drawn in)" sensory parameter, acquired by the processor in step ST153. [Figure 67] This is a scatter plot of the dynamic characteristics and expressiveness levels of each control device for the "feeling of recovery (or lack thereof)" sensory parameter acquired by the processor in step ST153. [Figure 68] This figure shows a list of correlation coefficients between each emotional parameter and each dynamic characteristic. [Figure 69] This is an example of a sequence diagram showing how a communication device and a terminal device communicate to estimate the sensory parameters of an attached operating device. [Modes for carrying out the invention]

[0013] The embodiments of this disclosure will be described below with reference to the drawings. In this specification and the drawings, components having substantially the same function will be denoted by the same reference numerals, and redundant explanations will be omitted. [Aspect 1] (Sensory control system) Figure 1 shows the basic configuration of a sensory control system 100 according to Embodiment 1 of the present disclosure. The sensory control system 100 shown in Figure 1 includes a sensibility database 16, a storage unit 11, an input unit 4, a processor 101, and a sensory presentation unit 102. The storage unit 11 stores a sensibility parameter-physical parameter conversion model (hereinafter simply referred to as "conversion model 15"). The sensory presentation unit 102 is a component that presents sensations to a person, and can be composed of, for example, a tactile presentation unit that presents touch (for example, a tactile presentation unit 30 described later), an auditory presentation unit such as a speaker that presents hearing, a visual presentation unit such as a display device that presents sight, or any combination thereof.

[0014] The conversion model 15 is a conversion model that can convert a sensibility parameter into a physical parameter that correlates with that sensibility parameter. Here, the sensibility parameter is a parameter that indicates the degree of sensory expression in response to a sensory presentation. Specifically, in the case of sensibility evaluation using the Semantic Differential Method (SD), the sensibility parameter may be a multi-level evaluation indicating which of two sensory expressions (adjectives, onomatopoeia, sound symbolic words, etc.) the presented sensation is closer to. Specifically, the combination of two sensory expressions may be "pleasant-unpleasant" or "light-heavy". In the multi-level evaluation using the SD method, for example, the expression frequency of the sensibility parameter for "most pleasant" can be set to "1", and as the expression frequency increases to "2", "3", "4", etc., it moves towards "unpleasant", with "7" being "most unpleasant". The sensibility parameter is not limited to a combination of two sensory expressions, but may also be the intensity of a single sensory expression. Furthermore, it may be a multi-dimensional parameter expressed by taking multiple axes for sensory expression and combining these multiple axes. Physical parameters are included in the physical properties related to sensory presentation and there are multiple types. The physical properties related to sensory presentation are physical properties that can affect the entire sensory transmission system, including the sensory presentation means such as the sensory presentation unit 102 and the body parts of the person, when presenting sensations to a person. In other words, the physical properties related to sensory presentation are not limited to the physical properties of the sensory presentation means, but may also include the physical properties of the body parts of the person to which the sensations are presented.

[0015] Here, the affective database 16 is described as being stored in a storage unit other than the memory unit 11 (not shown), but the affective database 16 may also be stored in the memory unit 11. The processor 101 controls the operation of the entire sensory control system 100. The processor 101 is a general term for one or more processors, and for example, each component of the sensory control system 100 may be controlled by multiple processors, or all components may be controlled by one processor. Furthermore, each component of the sensory control system 100 only needs to be able to communicate information with each other in order to execute the conversion model generation method and sensory control method described later, and the connection method is not particularly limited. For example, the connection method for each component of the sensory control system 100 may be a wired connection or a wireless connection including a network connection. The sensory control system 100 may consist of multiple devices or it may be a single device.

[0016] The conversion model 15 included in the sensory control system 100 is obtained by the following conversion model generation method. In the conversion model generation method, first, the affective database 16 stores correspondence information for one or more types of sensory presentations, where the physical characteristics related to a given sensory presentation are associated with affective parameters indicating the degree of sensory expression for that sensory presentation (storage step). Based on the correspondence information for one or more types of sensory presentations in the affective database 16, the processor 101 extracts physical parameters that correlate with the affective parameters from among multiple types of physical parameters included in the physical characteristics related to the sensory presentation (extraction step). Subsequently, the processor 101 generates the conversion model 15 based on the affective parameters and the extracted physical parameters (generation step). The conversion model 15 thus generated is a conversion model capable of converting newly received affective parameters into physical parameters that correlate with those affective parameters. The sensory control system 100 functions as a conversion model generation system when executing the above-described conversion model generation method. In the extraction step, in order to derive multiple types of physical parameters included in the physical properties related to sensory presentation, it is possible to extract them from the physical properties related to the sensory presentation means, or from the physical properties of a system including human body parts.

[0017] The conversion model generation method may be performed by a conversion model generation system separate from the sensory control system 100. In this case, the conversion model generation system includes at least a sensibility database 16 and a processor 101. The sensory control system 100 may acquire the conversion model 15 obtained by the other conversion model generation system performing the conversion model generation method and store it in the storage unit 11. In this case, the sensory control system 100 does not need to have a sensibility database 16.

[0018] Furthermore, the aforementioned correspondence information stored in the sensibility database 16 may be updatable, and the conversion model 15 may also be updatable based on the updated correspondence information. Specifically, in the storage step of the conversion model generation method, the sensibility database 16 adds or updates the aforementioned correspondence information for one or more types of sensory presentations. Next, in the extraction step, the processor 101 extracts physical parameters correlated with sensibility parameters again based on the correspondence information for each of the one or more types of sensory presentations in the sensibility database 16. Then, in the generation step, the processor 101 updates the conversion model 15 based on the sensibility parameters and the newly extracted physical parameters.

[0019] The sensory control system 100 performs the following sensory control method. First, the sensory control system 100 receives input of affective parameters from a user or the like via the input unit 4 (reception step). Then, the processor 101 converts the received affective parameters into physical parameters that correlate with the affective parameters from among several types of physical parameters included in the physical characteristics related to sensory presentation, based on the conversion model 15 (conversion step). The processor 101 then generates a sensory presentation signal based on the converted physical parameters and outputs it to the sensory presentation unit 102 (output step). The sensory presentation unit 102 presents a sensation to the user or the like based on the sensory presentation signal (sensory presentation step).

[0020] Thus, the sensory control system 100 can present sensations to the user based on sensory presentation signals that are correlated with the received affective parameters, and can therefore present sensations that reflect human sensibilities to the user.

[0021] (Haptic control system 1) Figure 2 shows the configuration of the tactile control system 1 as a first embodiment of the sensory control system 100 shown in Figure 1, along with the signal flow.

[0022] The tactile control system 1 shown in Figure 2 has a main control unit 10. The main control unit 10 is a personal computer or server, and has a processor (CPU) 14 and a memory unit 11 containing RAM or ROM. The main control unit 10 is equipped with arithmetic function units 12 and 13 that are executed by the processor 14.

[0023] The haptic control system 1 shown in Figure 2 has an input / output device 3. The input / output device 3 includes an input unit 4, a display unit 5, and a processor that operates the input unit 4 and the display unit 5. The input / output device 3 and the main control unit 10 are connected via various interfaces.

[0024] The haptic control system 1 includes a haptic presentation device 20. The haptic presentation device 20 includes a terminal processor 18 that controls its operation. The arithmetic function unit 13, which functions as the output unit of the main control unit 10, and the haptic presentation device 20 are connected via cables and connectors, USB (Universal Serial Bus), HDMI (High-Definition Multimedia Interface, registered trademark), Ethernet (registered trademark), Wi-Fi, and other interfaces.

[0025] The memory unit 11 of the main control device 10 shown in Figure 2 stores a conversion model 15. As described in the explanation of the sensory control system 100 in Figure 1, the conversion model 15 is a conversion model that can convert received sensory parameters into physical parameters correlated with those sensory parameters. In this example, the sensory parameters are parameters that indicate the degree of sensory expression in response to tactile presentation. For example, the sensory parameters in this example may be those evaluated by the user in terms of sensory expression, representing the feel of operating a predetermined operating tool. In other words, the sensory parameters in this example are input in accordance with the operation of the predetermined operating tool. The physical parameters in this example are included in the physical characteristics related to tactile presentation and there are multiple types. For example, the physical parameters in this example may be physical parameters included in the physical characteristics that realize tactile presentation when a predetermined operating tool is operated. The physical parameters in this example can be used to operate the tactile presentation device 20 to reproduce the sensory expression of a predetermined operating tool.

[0026] The haptic presentation device 20 comprises at least a haptic presentation unit 30. Based on haptic presentation signals, the haptic presentation device 20 controls the haptic presentation unit 30 to present tactile sensations to the user. Here, the haptic presentation unit 30 is an example of the sensory presentation unit 102 shown in Figure 1.

[0027] The tactile presentation unit 30 may present tactile sensations by generating resistance or vibration. Examples of the tactile presentation unit 30 that generates resistance or vibration include a voice coil motor (VCM), a linear actuator (either resonant or non-resonant type), a piezoelectric element, an eccentric motor, a shape memory alloy, a magnetorheological fluid, and an electroactive polymer.

[0028] The tactile presentation unit 30 may present touch by presenting hot or cold sensations. An example of a tactile presentation unit 30 that presents hot or cold sensations is a Peltier element. A Peltier element utilizes the heat transfer of the Peltier effect when a direct current is applied to two opposing metal plates, and the amount of heat on the surface of the metal plates changes depending on the direction of the current. By controlling the direction and amount of current, it is possible to make the user feel a warm or cold temperature on a body part such as their finger that touches the Peltier element.

[0029] The tactile presentation unit 30 may present touch by applying electrical stimulation. An example of a tactile presentation unit 30 that provides electrical stimulation is a configuration that provides electrical stimulation by capacitive coupling with a body part such as the user's fingertip. The tactile presentation unit 30 may also present aerial touch. An example of a tactile presentation unit 30 that presents aerial touch is a configuration that presents touch by generating air vibrations using ultrasound or the like, causing a body part such as the user's fingertip to resonate with these air vibrations.

[0030] As shown in Figure 2, the haptic control system 1 may include an operating device 33, and the haptic presentation unit 30 may present tactile sensations to the user operating the operating device 33. The haptic presentation unit 30 may present a predetermined operating sensation by presenting tactile sensations to the user operating the operating device 33. Specifically, the haptic presentation unit 30 may present an operating sensation that mimics the operating sensation of a predetermined operating tool. For example, examples of operating tools whose operating sensations are to be mimicked include a push switch that accepts pressing operations, a rotary switch that accepts rotational operations, a joystick that accepts tilting operations, a slide switch that accepts sliding operations to a slide operation unit, and a touch panel that accepts contact operations, pressing operations, tracing operations, etc.

[0031] The operating device 33 can be any form that is capable of performing operations similar to the predetermined operating tool described above. Specifically, the operating device 33 may be in a form that mimics the predetermined operating tool, or it may be in a form unrelated to the predetermined operating tool, such as an operating device such as an operating glove that is worn on the user's hand and accepts operations by finger movements.

[0032] Furthermore, the tactile presentation unit 30 may present tactile sensations to the user independently of the operation of the operating device 33. In that case, the tactile control system 1 does not need to be equipped with the operating device 33.

[0033] As shown in Figure 2, the tactile presentation device 20 may be equipped with various sensors such as a position sensor 27 and an acceleration sensor 28. By being equipped with various sensors, the tactile presentation device 20 can detect at least one physical quantity of the tactile presentation device 20 itself, the operating device, and the user's body part, and control the driving of the tactile presentation unit 30 based on that physical quantity. In addition to the above, other sensors that can be used include, for example, a torque sensor, an angular velocity sensor, a temperature sensor, a pressure sensor (including a barometric pressure sensor), a humidity sensor, a magnetic sensor, a light sensor, an ultrasonic sensor, an electromyography sensor, etc.

[0034] [An example of a tactile presentation unit 30] Referring to Figures 3 to 5, an example of the tactile presentation unit 30 included in the tactile control system 1 according to this embodiment will be described. The tactile presentation unit 30 illustrated in Figures 3 to 5 reproduces the tactile sensation when operating a press-type operating tool. The model press-type operating tool is a press-type operating tool such as a tact switch (registered trademark) in which a disc-shaped leaf spring or a dome-shaped leaf spring generates an operating reaction force. The tactile presentation unit 30 reproduces a tactile sensation corresponding to the desired sensory parameters based on a tactile presentation signal provided by the main control device 10. By incorporating the tactile presentation unit 30 into the electronic circuits of various devices, this tactile presentation unit 30 can be used as a press-type operating tool that realizes a tactile sensation (in this case, an operating feel) corresponding to the desired sensory parameters, in place of an actual press-type operating tool. Furthermore, by reproducing the operating reaction force with the tactile presentation device 20, it is possible to evaluate the relationship between the sensory parameters that express the operating feel and the physical parameters included in the physical characteristics that operate the tactile presentation device 20, and use this evaluation as a guideline when designing a press-type operating tool.

[0035] Figure 4 shows an equivalent model illustrating an example of the components of the haptic presentation unit 30. Figure 5 shows the equivalent circuit and internal structure of the actuator 39 included in the haptic presentation unit 30. The arrow F shown in Figure 5 indicates the operating reaction force (vector quantity). In Figure 3, the operating principle of the haptic presentation unit 30 is explained using an equivalent circuit with Laplace transform operators.

[0036] As shown in Figure 4, the tactile presentation unit 30 may have a movable part 21. In this case, the operating device 33 shown in Figure 2 is integrated with the movable part 21 shown in Figure 4. Alternatively, the operating device 33 may be provided outside the system of the tactile presentation unit 20, and the movable part 21 may be moved by operating the operating device 33. The tactile presentation unit 30 has an actuator 39. As shown in Figure 5, the actuator 39 is provided with a bobbin 24 and a coil 25 wound outside the bobbin 24. The bobbin 24 and coil 25 are also part of the movable part 21.

[0037] As shown in Figure 4, the tactile presentation unit 30 may include a spring member 26. The spring member 26 has a predetermined spring constant and is composed of, for example, a coil spring. The spring member 26 is held in a compressed state within the tactile presentation unit 30, and under normal use conditions, it provides an operating reaction force in the opposite direction to the direction in which the movable part 21 is pressed (upward in Figure 4). In Figure 4, the spring constant of the spring member 26 is indicated by "Ks". As shown in Figure 4, the movable part 21 is subjected to an operating reaction force based on the viscosity coefficient "C" caused by lubricating oil or sliding friction on the mechanism. Also in Figure 4, the stroke amount of the movable part 21 in the direction in which it is pressed (downward in Figure 4) is indicated by "x".

[0038] As shown in Figure 5, the actuator 39 includes a cylindrical yoke 31 made of an iron-based magnetic material. The yoke 31 has an outer yoke 31a and a center yoke 31b. A cylindrical magnet 32 ​​is fixed inside the outer yoke 31a. A cylindrical magnetic gap is formed between the center yoke 31b and the magnet 32, and a cylindrical bobbin 24 and a coil 25 are inserted into the magnetic gap. As shown in Figure 5, the amount of current flowing through the coil 25 is "I", the magnetic flux density of the magnetic field emitted from the magnet 32 ​​and crossing the coil 25 is "B", the inductance of the coil 25 is "L", and the electrical resistance including the coil 25 is "R". The number of turns of the coil 25 is "N". The operating reaction force "F" acting from the actuator 39 on the movable part 21 is controlled by a tactile presentation signal provided from the main control device 10 to the tactile presentation device 20.

[0039] In this example, the position sensor 27 of the haptic presentation device 20 shown in Figure 2 detects the amount of movement (hereinafter referred to as "stroke amount") "x" of the movable part 21 in the pressing operation direction. In this example, the acceleration sensor 28 of the haptic presentation device 20 shown in Figure 2 detects the acceleration of the movable part 21. In this example, the variable operating range unit 29 of the haptic presentation device 20 shown in Figure 2 can change the total length of the stroke amount of the movable part 21 in the pressing operation direction.

[0040] The basic operation of the tactile feedback device 20 will be explained with reference to Figures 3 to 5. The tactile feedback device 20 can provide tactile feedback to the movable part 21 via the operating device 33 by controlling the current "I" supplied to the coil 25 of the tactile feedback unit 30. Here, the tactile feedback is a change in the operating reaction force "F" applied to a body part such as the user's finger that is pressing the movable part 21 in the pressing direction. This operating reaction force "F" is a resistance force that reproduces the operating reaction force of a pressing-type operating tool that generates the operating reaction force using a disc-shaped leaf spring or a dome-shaped leaf spring.

[0041] Figure 4 shows a model of the tactile presentation unit 30. The following equation 1 expresses the operation of the tactile presentation device 20 as a "force" equation.

[0042]

number

[0043] The following is equation 2, which is obtained by rearranging equation 1.

[0044]

number

[0045] In the equivalent circuit of the tactile presentation unit 30 shown in Figure 5, the voltage acting on the coil 25 is represented by "V", and the back electromotive force acting on the coil is represented by "e". Equation 3 below shows the differential equation for "Ve" and the equation obtained by expressing this differential equation using the Laplace transform variable "s".

[0046]

number

[0047]

number

[0048] [Conversion Model 15 Generation Process] Figure 6 shows an example of the process for generating the conversion model 15 stored in the haptic control system 1 of Figure 2 (conversion model generation method). The conversion model generation method is performed by a conversion model generation system comprising at least an input unit, a storage unit, and a processor. In Figure 6, "ST" indicates a processing step.

[0049] In STa, the conversion model generation system accepts input of affective parameters from multiple users for each of the one or more types of haptic presentations. Here, "one or more types of haptic presentations" includes not only the tactile sensations when the user operates a control device, but also the tactile sensations given to the user when the user does not operate anything. For example, one or more types of tactile sensations may be presented as haptic presentations corresponding to content such as games or videos via a suit or gloves, and input of affective parameters based on the user's perception of each may be accepted. This step is an example of a memory step in the conversion model generation method described for the sensory control system 100 in Figure 1.

[0050] In STb of Figure 6, the transformation model generation system extracts physical parameters that correlate with the affective parameters from among the physical properties related to various tactile presentations. This step is an example of the extraction step in the transformation model generation method described for the sensory control system 100 in Figure 1. In STc, the transformation model generation system generates a transformation model 15. This step is an example of the generation step in the transformation model generation method described for the sensory control system 100 in Figure 1. The transformation model 15 can be generated manually, by multiple regression analysis, machine learning, or various other analytical methods. The transformation model 15 has various variations, such as a model that can convert from one type of affective parameter to one type of physical parameter, a model that can convert from one type of affective parameter to multiple types of physical parameters, a model that can convert from multiple types of affective parameters to one type of physical parameter, and a model that can convert from multiple types of affective parameters to multiple types of physical parameters. A model that can convert from multiple types of affective parameters to multiple types of physical parameters may be generated by deriving information on complex correlations from information on the correlation between one type of affective parameter and one type of physical parameter using machine learning or the like. The data structure of the conversion model 15 may be a correspondence table between affective parameters and tactile parameters, or it may be stored in a way that allows it to be calculated by a function.

[0051] Here, we will describe an example of a method for generating a conversion model 15 that can convert from multiple types of emotional parameters to multiple types of physical parameters. In this example, first, the conversion model generation system extracts information on the correlation between each of the multiple types of physical parameters and the emotional parameters in the extraction step. Specifically, the conversion model generation system extracts the above-mentioned information on the multiple correlations by performing a multiple regression analysis in which each of the multiple types of emotional parameters is the dependent variable and the multiple types of physical parameters are the independent variables. Here, the information on correlations can be, for example, the coefficient of determination, the constant term in the multiple regression analysis, or values ​​derived from these.

[0052] Next, in the generation step, the transformation model generation system generates a first relational expression that explains each of the multiple types of affective parameters using multiple types of physical parameters and multiple correlation information (first generation step). Specifically, the multiple types of affective parameters are A1, A 2、 ···A n Let n be a natural number, and let there be multiple types of physical parameters P1, P2, ...P n In the multiple regression analysis, the constant term and coefficient of determination of the affective parameter A m (where m is a natural number less than or equal to n) is related to B m1 B m2 ,···B mn Therefore, the first relation can be expressed by the following number 5.

[0053]

number

[0054] If we express equation 5 as a matrix equation where one side (the left side) is a column vector representing multiple types of emotional parameters, and the other side (the right side) is the product of a coefficient matrix representing information on multiple correlations and a column vector representing multiple types of physical parameters, then the first relation is expressed as shown in Figure 22. Here, the coefficient matrix is ​​an n x n square matrix.

[0055] The transformation model generation system, after the first generation step included in the generation step, generates a second relational expression that explains each of the multiple types of physical parameters, based on the first relational expression and using information on multiple types of affective parameters and multiple correlations (second generation step). Specifically, the transformation model generation system generates the second relational expression by multiplying both sides of the first relational expression shown in Figure 22 by the inverse of the coefficient matrix from the left. As shown in Figure 23, the second relational expression can be expressed with column vectors representing the multiple types of physical parameters as one side (the left side here) and the product of the inverse of the coefficient matrix and the column vectors representing the multiple types of affective parameters as the other side (the right side here).

[0056] After the second generation step included in the generation step, the conversion model generation system generates a conversion model 15 that can convert multiple types of emotional parameters into multiple types of physical parameters correlated with those multiple types of emotional parameters, based on the second relational expression (third generation step). In this way, the conversion model generation system can generate a conversion model 15 that can convert multiple types of emotional parameters into multiple types of physical parameters.

[0057] In the example above, we assumed that the coefficient matrix was a square matrix, but the coefficient matrix does not necessarily have to be a square matrix. For example, by using a pseudo-inverse matrix as the inverse matrix, a conversion model 15 capable of converting from multiple types of emotional parameters to multiple types of physical parameters can be generated even when the coefficient matrix is ​​not a square matrix.

[0058] The sensory control method using the sensory control system 100 shown in Figure 1 can be implemented as follows when using the conversion model 15 obtained in this example. First, in the reception step, the sensory control system 100 receives input of multiple types of sensory parameters from the user or the like via the input unit 4. Then, in the conversion step, the processor 101 converts the acquired multiple types of sensory parameters into multiple types of physical parameters that correlate with those multiple types of sensory parameters, based on the conversion model 15. The output step and sensory presentation step are the same as described above, so their explanation is omitted.

[0059] [Specific examples of tactile presentation] The following describes an example in which the haptic presentation device 20 shown in Figure 2 provides haptic presentation that mimics the feel of operating a predetermined operating tool. In this example, the sensibility parameters of the conversion model 15 are the expressive frequencies of adjectives that describe the feel of operating a pressure-type operating tool, which is the predetermined operating tool. In this example, the physical parameters of the conversion model 15 are included in the physical characteristics that realize the sensory presentation when the pressure-type operating tool, which is the predetermined operating tool, is operated. When the haptic control system 1 receives input of specific sensibility parameters via the input unit 4, it uses the conversion model 15 to convert the received specific sensibility parameters into physical parameters. The sensibility parameters assuming a pressure-type operating tool are the degree of sensory expression using adjectives, onomatopoeia, etc., that describe the feel of operating the pressure-type operating tool when a person presses it. The physical characteristics realized by the physical parameters are, for example, the displacement associated with the operation (e.g., stroke amount), the operating reaction force (load), the speed of the movable part 21, acceleration, jerk, the elastic characteristics of body parts such as the operator's fingers, or quantities derived from these physical characteristics. In this specification, physical parameters are defined as those that include one or more variables of a physical property.

[0060] Figure 7 is a flowchart illustrating specific examples of a conversion model generation method and a haptic presentation method. In the flowchart shown in Figure 7, processing steps are indicated by "ST," where ST1, ST2, etc., include manual processing, and ST3, ST4, etc., include processing performed by the processor 14 of the main control unit 10 shown in Figure 2.

[0061] In ST1 in Figure 7, multiple operating tools with the same function but different operating sensations are prepared. In ST2, sensory tests are conducted by multiple users, and the operating sensations of the prepared multiple operating tools are classified by the expressive frequency of adjectives as sensory parameters. In ST3, the processor 14 of the tactile control system 1 associates the expressive frequency of adjectives as sensory parameters with physical parameters included in the physical characteristics that realize sensory presentation when the operating tool is operated, based on correlation coefficients, etc. Each of the sensory parameters and physical parameters contains at least one variable. The associated sensory parameters and physical parameters are stored as the sensory database 16 shown in Figure 1. In ST4, the processor 14 uses the conversion model 15 to convert the newly accepted input into physical parameters correlated with the expressive frequency of adjectives as sensory parameters. The calculation function unit 12 generates a tactile presentation signal based on the physical parameters, and the calculation function unit 13 outputs the tactile presentation signal. This tactile presentation signal activates the tactile presentation device 20, and tactile sensations are presented. By controlling at least one of the coefficients "Kv", "Ks", and "C" shown in Figure 4 using tactile presentation signals based on physical parameters, tactile sensations corresponding to the affective parameters are presented via the tactile presentation device 20.

[0062] In ST1 of Figure 7, for example, multiple push-type operating devices, such as tact switches (registered trademark), which are actual products having a disc-shaped leaf spring or a dome-shaped leaf spring, are prepared as operating devices. Figure 11 schematically shows the change in operating reaction force when a push-type operating device is pressed. Figure 11 shows the physical characteristics that realize sensory presentation when a push-type operating device is operated, on a coordinate plane in which the horizontal axis represents the change associated with the operation and the vertical axis represents the operating reaction force (load) acting on the body part of the user, such as the finger, performing the operation. In this specification, "change associated with the operation of the operating device" includes the amount of operation of the operating device, the operation time of the operating device, or a combination of the amount of operation and the operation time. That is, the physical characteristics that realize sensory presentation when the operating device is operated can be expressed in terms of the relationship between the amount of operation of the operating device and the operating reaction force, the relationship between the operation time of the operating device and the operating reaction force, or the relationship between the combination of the amount of operation and the operation time of the operating device and the operating reaction force. Furthermore, "transition associated with the operation of the operating tool" may also include transitions caused by the elastic properties of body parts such as the fingers of the operator operating the operating tool. In Figure 11, "transition associated with the operation of the operating tool" is the amount of operation of the press-type operating tool, and will be referred to as "stroke amount "x"" as appropriate below. The amount of operation of the operating tool is a quantity in one-dimensional space, two-dimensional space, or three-dimensional space. In Figure 11, the amount of operation of the press-type operating tool is a quantity in one-dimensional space along the direction of the press operation. Note that the operating tool may have a movable part that moves in conjunction with the operation of the operating tool. The press-type operating tool has a knob that is pressed by the user as a movable part. Therefore, the amount of operation of the press-type operating tool may also be the amount of movement of the movable part of the press-type operating tool.

[0063] As shown in Figure 11, the curve representing the physical characteristics that provide sensory feedback when an operating tool is operated, on a coordinate plane with the operating amount (movement of the movable part) of the operating tool on the horizontal axis and the operating reaction force on the vertical axis, is called the FS curve (Force Stroke Curve), feeling curve, operating force curve, load displacement curve, etc. Hereinafter, it will be referred to as the "load displacement curve" as appropriate. As shown in Figure 11, when a user presses a push-type operating tool, the operating reaction force gradually increases as the stroke amount "x" in the direction of the press operation increases, due to the compressive deformation of the disc-shaped or dome-shaped leaf spring. When the stroke amount "x" reaches the maximum position Pmax, the operating reaction force reaches its maximum value Tmax. When the push-type operating tool is pressed further, the disc-shaped or dome-shaped leaf spring buckles and reverses, causing the operating reaction force to decrease sharply. When the stroke amount "x" reaches the minimum position Pmin, the operating reaction force reaches its minimum value Tmin. Subsequently, when the user further presses the pressure-type operating tool, the buckled disc-shaped or dome-shaped leaf spring is compressed, and the operating reaction force continues to increase until it reaches the final stroke position where the disc-shaped or dome-shaped leaf spring contacts the fixed contact point. In Figure 11, the stroke at which the operating reaction force equals the maximum value Tmax during the push from the minimum position Pmin to the final position is defined as the load recovery position Pend.

[0064] After the user fully pushes the press-type operating tool to the final stroke position where the contacts make contact, and then releases the pressure on the press-type operating tool, the knob portion, which is the movable part of the press-type operating tool, returns to its initial position due to the elastic restoring force of the disc-shaped or dome-shaped leaf spring. The load displacement curve when the operating device 33 returns has hysteresis with respect to the load displacement curve when the displacement associated with the pressing operation is increased, as shown in Figure 11. For the sake of explanation, the operation will be described below using only the load displacement curve when the displacement associated with the pressing operation is increased.

[0065] Multiple (23 in total) press-type operating tools were classified into three groups (A), (B), and (C) according to the total stroke length when fully pressed down. Group (A) has a total stroke length of 0.25 mm or more and 0.35 mm or less, Group (B) has a total stroke length of 0.15 mm or more and less than 0.25 mm, and Group (C) has a total stroke length of less than 0.15 mm.

[0066] A sensory evaluation was conducted with 25 users for the aforementioned multiple types of pressure-type operating devices. In the sensory evaluation, the operating sensation (tactile sensation) felt by the users was classified using the Semantic Differential (SD) scale. In this sensory evaluation, a predetermined sensory parameter A was used as the sensory parameter and evaluated on a 7-point scale from "1", "2", "3", "4", "5", "6", and "7". In this sensory evaluation, the pressure-type operating devices in classification (A) showed a wide variation in the expression degree of sensory parameter A, ranging from around "1" to around "6". The pressure-type operating devices in classification (B) showed a variation in the expression degree of sensory parameter A in the intermediate range, ranging from around "2.5" to around "3.5". The pressure-type operating devices in classification (C) showed a variation in the expression degree of sensory parameter from around "3.5" to around "6". Here, the sensory parameter A is, for example, a parameter related to "decisiveness," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "decisiveness," a smaller expression frequency may indicate a "higher sense of decisiveness," and a larger expression frequency may indicate a "lower sense of decisiveness."

[0067] As described above, the correlation between the sensory parameter A and the total stroke amount of the press-type operating tool as a physical parameter is not always clear. Therefore, for the 23 press-type operating tools described above, we focused on physical characteristics other than the classified total stroke amount and examined whether there was a correlation between the physical parameters extracted from those physical characteristics and the sensory parameter A. Figure 9 shows the load displacement curves (i), (ii), and (iii) of three press-type operating tools with different total stroke amounts. In Figure 10(A), the area S4-1 of the depression in load displacement curve (i) and the area S4-2 of the depression in load displacement curve (ii) are extracted as variables of the physical quantity of the operation, and in Figure 10(B), the areas S4-1 and S4-2 are compared by shifting them parallel so that their respective minimum values ​​Tmin coincide.

[0068] As shown in Figure 11, area S4 is the area of ​​the depression in a coordinate plane where the amount of operation of the operating tool is on the horizontal axis and the operating reaction force is on the vertical axis, from the maximum value Tmax to the minimum value Tmin and then back to the same operating reaction force as the maximum value Tmax. In other words, area S4 is the area of ​​the region demarcated in the above coordinate plane by the load displacement curve and a straight line passing through the maximum value Tmax of the load displacement curve and parallel to the horizontal axis. The dimension representing area S4 is expressed as "(stroke amount) distance × (operating reaction force) load", and this dimension is equivalent to energy (work). That is, area S4 corresponds to the energy that is reduced (energy lost) compared to the energy consumption that the user foresaw, due to the decrease in operating reaction force when the user operates the press-type operating tool. Due to the existence of area S4, the user will feel a sensation of being pulled in the direction of the press operation.

[0069] In Figure 9, the operating reaction force shown by the load-displacement curve (iii) has a preload when the stroke is zero. This preload creates what is known as "play" in operation. This "play" can also be considered as one of the physical parameters.

[0070] Figure 12 is a graph showing the relationship between the emotional parameter A, which is the degree of expression measured by the Semantic Differential (SD) method, and the area S4, which is a physical parameter extracted from the physical characteristics that realize sensory presentation when the operating tool is operated. In Figure 12, the horizontal axis represents the emotional parameter A, and the vertical axis represents the area S4, which is a physical parameter. As shown in Figure 12, for a total of 23 press-type operating tools with a total stroke length of 0.35-0.15 mm, it can be seen that there is a correlation between the size of the area S4 shown in Figure 11 and the degree of expression of the emotional parameter A. In other words, for the 23 press-type operating tools, it can be seen that there is a negative correlation, where the degree of expression of the emotional parameter A decreases as the area S4 increases. Here, when there is a correlation between the emotional parameter and the physical parameter, the absolute value of the correlation coefficient between the emotional parameter and the physical parameter is preferably 0.5 or higher, and more preferably 0.7 or higher.

[0071] For normalizing the physical quantity of area S4, it is preferable to limit the total stroke length of the press-type operating tool to a predetermined range. For example, the total stroke length of the press-type operating tool is preferably 0.05 mm or more and less than 0.5 mm, and more preferably 0.05 mm or more and less than 0.35 mm.

[0072] Thus, in the above example, the change in the operating reaction force in response to the displacement associated with the operation of the operating tool has at least a maximum and a minimum. The physical parameters include variables based on the area of ​​the depression in the coordinate plane, where the displacement associated with the operation and the operating reaction force are axes, respectively, up to the coordinate where the operating reaction force transitions from the maximum to the minimum and then back to the same magnitude as the maximum. Here, the maximum is the portion containing the maximum value Tmax in the load-displacement curve shown in Figure 11, and the minimum is the portion containing the minimum value Tmin in the load-displacement curve shown in Figure 11.

[0073] The haptic control system 1 shown in Figure 2 uses a conversion model 15 to convert the expression frequency of the sensory parameter A received as input into an area S4, which is a physical parameter correlated with the sensory parameter A. The calculation function unit 12 then calculates a load-displacement curve that includes the area S4 and sets one haptic presentation signal that includes the load-displacement curve. Alternatively, the calculation function unit 12 calculates multiple load-displacement curves that have the same area S4 but differ in stroke, load, etc., and sets multiple haptic presentation signals that include these load-displacement curves. Or, the conversion model 15 may store in advance multiple types of load-displacement curves associated with the size of the area S4 in relation to the expression frequency of the sensory parameter A, and the calculation function unit 12 may read information on the load-displacement curve corresponding to the expression frequency of the sensory parameter A received as input from the storage unit 11 to generate a haptic presentation signal.

[0074] The input section 4 of the input / output device 3 can accept inputs of not only integer representation frequencies such as "2", "3", etc., or representation frequencies including decimals such as "2", "2.5", "3", "3.5", etc., but also numerical ranges of representation frequencies such as "2-2.5", "2.5-3", "3-3.5", "3.5-4", etc. The haptic control system 1 uses the conversion model 15 to convert one or more load-displacement curves having an area S4, which is a physical parameter corresponding to the representation frequency of the affective parameter received as input via the input section 4. The information of the converted one or more load-displacement curves is output to the input / output device 3, and the input / output device 3 displays one or more load-displacement curves on the display section 5. The user checks the single load-displacement curve displayed on the display section 5, or selects one of the multiple displayed load-displacement curves. When this confirmation command or selection command is given from the input unit 4 to the processor 14, the calculation function unit 12 sets a tactile presentation signal based on the selected load displacement curve, and the calculation function unit 13 outputs the tactile presentation signal to the tactile presentation device 20. As a result, when the operating device 33 of the tactile presentation device 20 is operated, the user can be presented with an operating sensation corresponding to the degree of expression of the desired sensory parameter.

[0075] Furthermore, as input items from the input unit 4, physical parameters such as "stroke amount" and "magnitude of operating reaction force" may be directly specified along with the expression frequency of the sensibility parameter A. For example, when the tactile control system 1 receives input of "stroke amount 0.25-0.35 mm" as a physical parameter along with the expression frequency of the sensibility parameter A via the input unit 4, it selects a load-displacement curve with an area S4 that matches the expression frequency of the adjective from among the multiple load-displacement curves included in classification (A), and generates a tactile presentation signal based on this load-displacement curve. Alternatively, when the tactile control system 1 receives input of a numerical item "magnitude of operating reaction force" as a physical parameter along with the expression frequency of the sensibility parameter A via the input unit 4, it may generate a tactile presentation signal based on both the expression frequency of the sensibility parameter A and the "magnitude of operating reaction force" as a physical parameter.

[0076] In the explanation so far, the total stroke amount has been limited to a range of, for example, 0.35-0.15 mm, and the physical parameter, which is the size of the area S4, and the emotional parameter, which is the expressive frequency of the adjective, have been associated with this range. However, the size of the area S and the expressive frequency of the emotional parameter may also be associated with a numerical range other than the range of the total stroke amount mentioned above. For example, a predetermined numerical range may be set using the maximum value Tmax, minimum value Tmin, maximum value minus minimum value (Tmax-Tmin), click stroke (Pend-Pmax), push stroke (Pmax / (Pend-Pmax)), click stroke ratio (Pmax / Pend), push stroke ratio (Pmax / (Pend-Pmax)) as shown in Figure 11, and this numerical range may be used as the basis. Alternatively, a predetermined numerical range may be set using areas S1, S2, S3 other than S4, or their ratios, and that numerical range may be used as the basis. Based on these numerical ranges, it is possible to correlate the size of the physical parameter, area S4, with the expressiveness level of the affective parameter.

[0077] Regarding the 23 pressure-type operating tools mentioned above, sensory tests of the operating feel were conducted with 25 users for sensory parameters other than sensory parameter A. The results are shown in Figures 13 to 15. Figures 13 to 15 show the relationship between the expressiveness of sensory parameters other than sensory parameter A and physical parameters other than area S4 that change according to that expressiveness.

[0078] Figure 13 shows the frequency of expression of the sensory parameter B on the horizontal axis. The vertical axis shows a variable related to the stroke amount of the press-type operating tool as a physical parameter, for example, the "click stroke (Pend-Pmax)" shown in Figure 11. Figure 13 shows a negative correlation where the frequency of expression of sensory parameter B decreases as the "click stroke (Pend-Pmax)" as a physical parameter increases. Sensory parameter B may be a parameter related to, for example, "sense of determination," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "comfort," a smaller frequency of expression may indicate "comfort," and a larger frequency of expression may indicate "discomfort."

[0079] Thus, in the example above, the physical parameters include variables relating to the amount of displacement associated with the operation. More specifically, they include the "click stroke (Pend-Pmax)," which is the amount of displacement from the point of maximum force to the coordinate where the operating reaction force transitions from the point of maximum force to the point of minimum force and then to the same magnitude as the point of maximum force.

[0080] Figure 14 shows the frequency of expression of the sensory parameter C on the horizontal axis. The vertical axis shows a variable related to the load of the press-type operating tool as a physical parameter, for example, Pmax shown in Figure 11. Figure 14 shows a positive correlation where the frequency of expression of the sensory parameter C decreases as Pmax as a physical parameter decreases. The sensory parameter C is a parameter related to, for example, "sense of determination," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "tactile sensation," a smaller frequency of expression may indicate that the operating sensation feels softer, and a larger frequency of expression may indicate that the operating sensation feels harder.

[0081] Figure 15 shows the frequency of expression of the sensory parameter D on the horizontal axis. The vertical axis is a variable related to the stroke amount of the press-type operating tool as a physical parameter, for example, the "push-in stroke ratio (Pmax) / (Pend-Pmax)" shown in Figure 11. Figure 15 shows a positive correlation in which the frequency of expression of the sensory parameter D increases as the "push-in stroke ratio (Pmax) / (Pend-Pmax)" as a physical parameter increases. The sensory parameter D is a parameter related to, for example, "sense of determination," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "tactile sensation," a higher frequency of expression may indicate that the tactile sensation is perceived as sharper, and a lower frequency of expression may indicate that the tactile sensation is perceived as duller.

[0082] Thus, in the above example, the physical parameters include variables related to the amount of displacement associated with the operation. More specifically, they include variables related to the "click stroke (Pend-Pmax)," which is the amount of displacement from the point of maximum force to the coordinate where the operating reaction force transitions from the point of maximum force to the point of minimum force, and the "push-in stroke ratio (Pmax) / (Pend-Pmax)," which is the ratio of "Pmax," the amount of displacement from the start of the operation to the point of maximum force.

[0083] In the conversion model 15, multiple relationships may be stored as correlations between affective parameters and physical parameters, including: (1) the relationship between the expressive frequency of affective parameter A shown in Figure 12 and the physical parameter area S4; (2) the relationship between the expressive frequency of affective parameter B shown in Figure 13 and the physical parameter click stroke; (3) the relationship between the expressive frequency of affective parameter C shown in Figure 14 and the physical parameter maximum value minus minimum value; and (4) the relationship between the expressive frequency of affective parameter D shown in Figure 15 and the physical parameter indentation stroke ratio. One or more of these relationships (1)-(4) are combined to calculate the physical parameters included in physical quantities such as load-displacement curves, and a tactile presentation signal is generated.

[0084] Incidentally, as mentioned above, the acceleration of the movable part 21 of the tactile presentation unit 30 shown in Figure 4 can be detected by the acceleration sensor 28. In actual press-type operating tools, when a disc-shaped or dome-shaped leaf spring is pressed, it buckles and deforms, and when it reverses, vibrations are generated and transmitted to the body part performing the pressing operation, such as the finger, thereby providing a tactile sensation.

[0085] Figures 16(A), (B), and (C) show simulation data illustrating the acceleration of the movable parts of three pressure-type operating tools when they are pressed. Sensory testing by users using the three pressure-type operating tools investigated the relationship between the expressive frequency of the sensory parameter E, related to the feel of the pressing operation, and the acceleration of the movable parts of the operating tool as a physical parameter. The peak-to-peak acceleration value when the disc-shaped or dome-shaped leaf spring of the pressure-type operating tool buckles is highest for the pressure-type operating tool in Figure 16(A), decreasing in the order of (B) and (C). Furthermore, in the sensory testing by users, the expressive frequency of the sensory parameter E for the operation of the pressure-type operating tool in Figure 16(A) was the lowest, increasing in the order of (B) and (C). The emotional parameter E may be a parameter related to, for example, "sense of determination," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "comfort," a smaller expression frequency may indicate "comfort," while a larger expression frequency may indicate "discomfort."

[0086] Based on the sensory tests described above, the conversion model 15 may store the correlation between the expression frequency of the sensory parameter E and the acceleration of the movable part of the operating tool, which is a physical parameter. The tactile control system 1 uses the conversion model 15 to convert the expression frequency of the sensory parameter E input by the input unit 4 into the acceleration of the movable part of the operating tool, which is a physical parameter, generates a tactile presentation signal based on this acceleration, and outputs the tactile presentation signal, thereby allowing the tactile presentation device 20 to reproduce the desired operating sensation. For example, a tactile presentation signal may be generated to control the corresponding physical parameter of the movable part 21 of the tactile presentation device 20 based on the physical parameter (amount of movement, velocity, acceleration, jerk, etc.) of the movable part of the operating tool.

[0087] [Example of operation of the tactile presentation device 20] Figure 8 shows a flowchart of an example of the control operation of the haptic presentation device 20. The processes shown in the flowchart are executed by the control operation of the processor 18 included in the haptic presentation device 20. In ST11 of Figure 8, a haptic presentation signal is provided from the calculation function unit 13 to the processor 18 of the haptic presentation device 20, and in ST12, control based on the load displacement curve selected based on physical parameters is started. In ST13, when the operating device 33 is operated, detection signals related to the movable part 21 are obtained from the position sensor 27 and the acceleration sensor 28. The processor 18 calculates the difference between the motion profile of the load displacement curve set in accordance with the expression degree, which is a sensibility parameter, and the detected position of the movable part 21. In ST14, the current I supplied to the coil 25 of the haptic presentation unit 30 is optimized, and tactile sensations are presented so that the expression degree of the sensibility parameter desired by the user can be reproduced.

[0088] [Modified version of the tactile presentation device 20] Referring to Figures 17 to 19, a modified example of the tactile presentation device 20 included in the tactile control system 1 will be described. The tactile presentation device 40 illustrated in Figure 19 reproduces the tactile sensation of a rotary operating device. The rotary operating device is, for example, a rotary switch.

[0089] The haptic presentation device 40 shown in Figure 19 comprises a processor 41, a haptic presentation unit 43, and a sensor 45. The haptic presentation device 40 provides tactile feedback to the user who rotates the operating device 42. The operating device 42 may be mechanically incorporated into the haptic presentation device 40 or may be provided outside the haptic presentation device 40.

[0090] The tactile feedback unit 43 includes a resistance torque generator 43a and a rotational torque generator 43b. The resistance torque generator 43a provides a variable resistance torque in the opposite direction to the rotational direction in response to the rotational operation of the rotational operation part of the operating device 42. The resistance torque generator 43a includes, for example, a yoke made of a magnetic material and a coil that applies a magnetic field to the yoke. A rotating plate that rotates in conjunction with the rotational operation of the rotational operation part of the operating device 42 is located within the magnetic gap of the yoke, and a magnetorheological fluid is filled between the yoke and the rotating plate within the magnetic gap. It is also possible to use magnetic powder instead of magnetorheological fluid. By controlling the current supplied to the coil, the aggregation state of the magnetorheological fluid changes, and the resistance torque is varied. In addition to the above configuration, the resistance torque generator 43a includes, for example, a rotary motor, and the resistance torque can be varied by the rotary motor. The rotational torque generator 43b provides a variable rotational torque in the rotational direction in response to the rotational operation of the rotational operation part of the operating device 42. The rotational torque generator 43b includes, for example, a rotary motor. The sensor 45 detects the rotation angle of the rotary operating part of the operating device 42.

[0091] Figure 18 shows the load-displacement curve related to the operating reaction force of a rotary switch, a rotary-type operating device. The rotary switch is divided into multiple division angles within its 360-degree (one rotation) range, and the operating reaction force changes within each division angle, with the same change in operating reaction force repeating within each division angle. Figure 18 shows the change in operating reaction force within one division angle. The horizontal axis of Figure 18 represents the rotation angle of the rotary operating part as the operating amount of the rotary switch, the positive side of the vertical axis represents the magnitude of the resistance torque acting on the rotary operating part of the rotary switch in the opposite direction to the operating direction, and the negative side of the vertical axis represents the magnitude of the rotational torque acting on the rotary operating part in the same direction as the operating direction. The rotary switch is provided with spring contacts within each division angle. When rotation is started within a division angle, the spring contacts contract, and the resistance torque acting on the rotary operating part increases. When the resisting torque exceeds its maximum value Rmax, the restoring force of the spring contact pushes the rotating part in the direction of rotation, reducing the resisting torque. Furthermore, a rotational torque directed in the direction of operation acts from the spring contact to the rotating part. As a result, when rotating the rotating part, a tactile sensation is obtained in the fingers at each segment angle.

[0092] The conversion model 15 stores the correlation between the expressiveness of the affective parameters related to rotational operation and the physical parameters. The haptic control system 1 receives input of the expressiveness of the affective parameters via the input unit 4. Subsequently, the processor 14 of the haptic control system 1 uses the conversion model 15 to convert the received affective parameters into physical parameters and generates a haptic presentation signal based on those physical parameters. The processor 14 then outputs the generated haptic presentation signal to the processor 41 included in the haptic presentation device 40 shown in Figure 19. When the rotational operation part of the operating device 42 is rotated by a body part such as the user's finger, the haptic presentation device 40 detects the rotation angle of the rotational operation part with a sensor 45 and feeds back the detection output to the processor 41. The haptic presentation unit 43 is controlled by the processor 41, which controls the resistance torque and rotational torque when the rotational operation part of the operating device 42 is rotated, and can present a tactile sensation that mimics a rotary switch, reproducing the expressiveness of the affective parameters.

[0093] Figure 17 is an explanatory diagram illustrating the change in resistance torque as an example of physical characteristics related to the expressiveness of the sensory parameter. Figure 17(A) shows the operating reaction force when four rotary switches are rotated, represented by a load-displacement curve, and Figure 17(B) shows the change in curvature on each of the load-displacement curves shown in Figure 17(A). Sensory tests by multiple users revealed that when the rotary operating part is rotated with a body part such as a finger, the resistance torque passes through a peak where it reaches a maximum value Rmax. It was concluded that the smaller the curvature of the change in the operating line at this peak, the higher the expressiveness of the sensory parameter F. In other words, it was confirmed that the expressiveness of the sensory parameter F correlates with the curvature of the inflection point where the rotational load transitions from increasing to decreasing. Therefore, by storing the correlation between the expressiveness of the sensory parameter F and a physical parameter whose variable is the curvature of the change in resistance torque, the tactile presentation device 40 can present a rotational operation sensation that realizes the expressiveness of the sensory parameter F as a tactile sensation. The sensory parameter F is, for example, a parameter related to "decision," "comfort," or "tactile sensation." Specifically, if it is a parameter related to "tactile sensation," it may be a parameter where a higher expressiveness indicates a sharper tactile sensation, and a lower expressiveness indicates a duller tactile sensation.

[0094] Thus, in the above example, the change in the operating reaction force with respect to the displacement associated with the operation of the operating tool has at least a maximum portion. Furthermore, the physical parameters include a variable relating to the curvature of the maximum portion, which includes the maximum value Rmax. Here, the maximum portion is the part of the load-displacement curve shown in Figure 18 that includes the maximum value Rmax.

[0095] Furthermore, as shown in Figure 18, physical parameters, including variables related to the rise in rotational load, such as the angle of the rise vector Tb of the resistance torque from the starting point of the division angle in the rotation angle as the operating amount of the rotary switch, and the ratio of the area Sa to Sb shown in the load-displacement curve at the rise portion of the resistance torque, can be associated with the frequency of expressions of adjectives such as "stiff operation" and "resistance," which are sensory parameters. Thus, in this example, the physical parameters include variables related to the rise in operating reaction force from the start of operation to the maximum portion.

[0096] Here, the area Sa shown in Figure 18 is the area demarcated by the load-displacement curve, the horizontal axis, and a straight line parallel to the vertical axis that passes through the intersection of the load-displacement curve and the maximum value Rmax. In other words, area Sa is the value obtained by integrating the load-displacement curve over the range of rotation angles from the starting point of the division angle in the rotation angle as the manipulated quantity to the maximum value Rmax of the operating reaction force. Area Sb is the area demarcated by the load-displacement curve, the vertical axis, and a straight line parallel to the horizontal axis that passes through the maximum value Rmax. In other words, area Sb is the area obtained by subtracting area Sa from the area of ​​a rectangle whose side is the rotation angle value at the intersection of the load-displacement curve and the maximum value Rmax, and whose other side is the maximum value Rmax. In other words, if the load-displacement curve changes linearly on the coordinate plane from the start of operation until the operating reaction force reaches its maximum value Rmax, as shown by the dashed line in Figure 18, then area Sa:area Sb = 1:1, and the smaller area Sb is relative to area Sa, the more the load-displacement curve bulges towards the positive side of the vertical axis on the coordinate plane. That is, the ratio of area Sa to area Sb indicates the degree of bulging of the load-displacement curve. Also, the rise vector Tb of the resistance torque as a physical parameter shown in Figure 18 includes a variable relating to the derivative of the operating reaction force with respect to the amount of operation. Similarly, the physical parameter may include a variable relating to the derivative of the operating reaction force with respect to the operation time, or a variable relating to the second derivative with respect to the change in the operating reaction force.

[0097] Furthermore, it is possible to associate the variable Dmax, the maximum value of the rotational torque (pull-in torque) acting in the same direction as the operating direction shown in Figure 18, that is, the magnitude of the pull-in amount at which the direction of the rotational load reverses, with the frequency of expressions such as "fast rotation." Thus, in this example, the physical parameters include a variable relating to the magnitude of the pull-in amount, where the minimum is negative. Here, the minimum is the portion containing the maximum value Dmax in the load-displacement curve shown in Figure 18.

[0098] In the example above, Figure 18 was explained as showing the load-displacement curve related to the operating reaction force of a rotary switch, which is a rotary-type operating device. However, Figure 18 can also be used to show the load-displacement curve related to the operating reaction force of a slide switch, which accepts sliding operations to a sliding operating part. That is, the horizontal axis of Figure 18 represents the amount of sliding operation of the sliding operating part, and the positive side of the vertical axis represents the operating reaction force to the sliding operation of the sliding operating part. The operating reaction force gradually increases with increasing sliding operation of the sliding operating part, reaches a maximum value Rmax, then decreases after exceeding the maximum value Rmax, and becomes a pulling force acting in the same direction as the operating direction, reaching a minimum value (maximum value on the negative side of the vertical axis) Dmax. In this way, the operating sensation can be presented in conjunction with the operation of the slide switch. The correlation between the sensory parameters and physical parameters described for the rotary switch is also the same for the slide switch.

[0099] [First modified example of the sensory control method] A first modification of the sensory control method performed by the sensory control system 100 of this disclosure further includes an acquisition step of acquiring a sensory stimulus signal and a designation step of specifying affective parameters based on the acquired sensory stimulus signal. Furthermore, the reception step of receiving the aforementioned affective parameters is not limited to input from a user or the like, but is a step of receiving the affective parameters specified in the designation step. As a result, the sensory control system 100 according to the first modification can specify affective parameters based on the acquired sensory stimulus signal and output a sensory presentation signal based on physical parameters correlated with the specified affective parameters.

[0100] Here, the sensory stimulus signal is an auditory stimulus signal based on an auditory stimulus element such as sound, a visual stimulus signal based on a visual stimulus element such as an image or video, a tactile stimulus signal based on a tactile stimulus element such as operating reaction force or vibration, or a signal based on any combination thereof. Furthermore, the sensory control system 100 according to the first modified example may generate and acquire sensory stimulus signals by sensing auditory stimulus elements, visual stimulus elements, tactile stimulus elements, or combinations thereof in the acquisition step.

[0101] Furthermore, in the first modified sensory control system 100, in the designated step, physical parameters included in the physical characteristics of at least one of the auditory, visual, and tactile stimulus elements (hereinafter collectively referred to as sensory stimulus elements) that form the basis of the sensory stimulus signal may be converted and designated as affective parameters to which the physical parameters correlate. When converting physical parameters to correlated affective parameters, the conversion model 15 described above may be used, or a conversion model different from the conversion model 15 may be used. A conversion model different from the conversion model 15 can be generated, like the conversion model 15, by AI analysis including machine learning, based on correspondence information stored in the affective database 16. In addition, physical parameters included in the physical characteristics of sensory stimulus elements such as sound, images, and videos can be extracted by AI analysis including machine learning.

[0102] As described above, the sensory control system 100 according to the first modified example can acquire sensory stimulus signals based on sensory stimulus elements such as sound, images, and videos, extract physical parameters included in the physical characteristics of the sensory stimulus elements through AI analysis, specify correlated affective parameters, and output a sensory presentation signal based on the physical parameters correlated with the specified affective parameters. Therefore, for example, it can output a tactile presentation signal with affective parameters adjusted based on sound, images, videos, etc.

[0103] [Second variation of the sensory control method] The operating device 33 of this disclosure may have an operating surface that accepts sliding operations. A sliding operation is an operation in which a user moves the contact position while keeping a body part such as their finger in contact with the operating surface of the operating device 33. In this case, the tactile presentation unit 30 of this disclosure generates an operating reaction force by vibrating the operating surface of the operating device 33. A method for vibrating the operating surface of the operating device 33 is, for example, by vibrating a weight using an actuator or the like. In the second modified example of the sensory control method of this disclosure, the sensory presentation step can be a step of presenting tactile sensation by using such an operating device 33 and tactile presentation unit 30 to generate an operating reaction force from the tactile presentation unit 30 in response to a sliding operation of the operating device 33. In detail, in the sensory presentation step, when a sliding operation is performed on the operating surface of the operating device 33, the operating device 33 detects the sliding operation and generates an operating reaction force from the tactile presentation unit 30 in response to the detected sliding operation.

[0104] The physical parameters that can be converted based on the conversion model 15 stored in the memory unit 11 of the sensory control system 100 according to the second modification include parameters relating to the change in operating reaction force with respect to the displacement associated with the sliding operation of the operating device 33, and the change in operating reaction force includes at least a maximum or minimum portion. Then, in the sensory presentation step, by controlling the tactile presentation unit 30 with a tactile presentation signal based on such physical parameters, it is possible to pseudo-synthesize the change in operating reaction force with respect to the displacement associated with the sliding operation of the operating device 33 to include the aforementioned maximum or minimum portion. Here, the tactile presentation unit 30 supplies a drive signal that generates vibration of the operating surface of the operating device 33 based on the received tactile presentation signal, driving the operating surface in a first direction on the rising edge of the drive signal and driving the operating surface in a second direction opposite to the first direction on the falling edge of the drive signal. Therefore, by making the rising and falling time changes of the drive signal different, and by making the power in the first direction corresponding to the rising or the second direction corresponding to the falling greater than the other over a predetermined time average, the aforementioned maximum and minimum portions can be pseudo-combined. Here, the drive signal that generates vibration of the operating surface of the operating device 33 may be, for example, a signal that drives a weight by an actuator, and the vibration of the weight may indirectly generate vibration of the operating surface.

[0105] Figure 24 shows an example of the time variation of the intensity of the drive signal supplied to the weight based on a tactile feedback signal. In the example shown in Figure 24, when the time variation of the drive signal intensity is positive, the weight is driven in a first direction, and when the time variation of the drive signal intensity is negative, the weight is driven in a second direction. As shown in Figure 24(a), if the time variation of the rising edge of the drive signal for the weight is greater than the time variation of the falling edge of the drive signal for the weight on average over a predetermined time, the power in the first direction corresponding to the rising edge of the drive signal will be greater than the power in the second direction corresponding to the falling edge of the drive signal. On the other hand, as shown in Figure 24(b), if the time variation of the falling edge of the drive signal for the weight is greater than the time variation of the falling edge of the drive signal for the weight on average over a predetermined time, the power in the first direction corresponding to the rising edge of the drive signal will be greater than the power in the second direction corresponding to the falling edge of the drive signal. Thus, by switching control between a period in which the power in the first direction is increased, as shown in Figure 24(a), and a period in which the power in the second direction is increased, as shown in Figure 24(b), the aforementioned maximum or minimum portions can be pseudo-combined.

[0106] The first and second directions may be directions that intersect with the operating surface of the operating device 33, or directions that are parallel to the operating surface. For example, if the first and second directions are directions that intersect with the operating surface of the operating device 33, the force resisting the pressing direction against the operating surface will change for body parts such as the user's fingers that slide on the operating surface, thereby changing the frictional force between the body part and the operating surface, i.e., the operating reaction force, associated with the sliding operation. Alternatively, if the first and second directions are directions that are parallel to the operating surface of the operating device 33, the force resisting the sliding direction on the operating surface will change for body parts such as the user's fingers that slide on the operating surface, thereby changing the frictional force between the body part and the operating surface, i.e., the operating reaction force, associated with the sliding operation.

[0107] Furthermore, the conversion model 15 stored in the memory unit 11 of the sensory control system 100 according to the second modified example may be obtained by a conversion model generation method that includes the following memory steps. That is, in the memory step of the conversion model generation method according to the second modified example, the sensory database 16 stores correspondence information for one or more types of operating tools, which associates the physical characteristics that realize sensory presentation when a predetermined operating tool is operated with the sensory parameters that are input reflecting the operation of the operating tool. Here, the operating tool has an operating surface that accepts sliding operation. Also, the change in operating reaction force with respect to the shift accompanying the sliding operation of the operating tool includes at least a maximum and a minimum portion. Here, the operating reaction force is generated by the vibration of the operating surface of the operating tool. The vibration of the operating surface of the operating tool may be an indirect vibration caused by, for example, the vibration of a weight by an actuator, similar to the vibration of the operating surface of the operating device 33 described above. The maximum or minimum portion of the change in operating reaction force in response to the movement accompanying the sliding operation of the operating tool is pseudo-combined by making the rising and falling time changes of the drive signal that causes vibration of the operating surface of the operating tool different, and by making the power in the direction corresponding to the rising or falling direction greater than the other over a predetermined time average. By using such an operating tool, the conversion model 15 in this example can be generated more easily.

[0108] [A variation of Sensory Database 16] As described above, the sensory database 16 of this disclosure stores correspondence information for one or more types of sensory presentations, where the physical characteristics related to a given sensory presentation are associated with sensory parameters indicating the degree of sensory expression for that sensory presentation. Although tactile presentations have been mainly described as sensory presentations, the term "touch" as primarily used in this specification refers to touch in a broad sense, and this broad sense of touch is a concept that includes touch in a narrow sense, pressure sensation, force sensation, etc. In this specification, when simply referred to as "touch," it means touch in a broad sense. Here, touch in a narrow sense is, for example, a sensation related to the texture of the surface of an object that a body part comes into contact with, and has a high correlation with sensory parameters related to sensory expression such as unevenness and roughness. Pressure sensation is, for example, a sensation related to the resistance force between a body part and an object, and has a high correlation with sensory parameters related to sensory expression such as hardness. Force sensation is, for example, a sensation related to external forces applied to a body part, such as the sensation of being pulled or pushed. It should be noted that the receptors primarily responsible for touch, pressure, and force sensations are different, and it is known that there are also differences in the response characteristics of each receptor.

[0109] Furthermore, the physical properties related to tactile presentation include static and dynamic properties. Static properties are the physical properties obtained when a control tool is operated at a constant operating speed using, for example, a device with high rigidity to the extent that elasticity is negligible (hereinafter simply referred to as "rigid body"). Dynamic properties are the physical properties obtained when a control tool is operated at a varying operating speed using, for example, a flexible material that mimics a body part such as a human finger. Unlike static properties, dynamic properties include physical parameters such as the elastic properties of the body part, operating speed, operating acceleration, operating jerk, and frictional force.

[0110] The correspondence information stored in the sensory database 16 may be information related to at least one of the following: information on touch, pressure, and force in the narrow sense, which are included in broad senses of touch; and information on static and dynamic properties included in physical properties. For example, the correspondence information stored in the sensory database 16 may be information in which the weighting of static and dynamic properties for touch, pressure, and force in the narrow sense changes depending on the stage of operation of the operating tool. More specifically, for example, in the operation stage immediately after starting the operation, the weighting of static properties may be set to be greater than the weighting of dynamic properties, and in the operation stage in which the change in operating reaction force with respect to the displacement accompanying the operation is large (for example, the operation stage corresponding to the maximum part in the load displacement curve shown in Figures 11 and 18, or the minimum part in the load displacement curve shown in Figure 11), the weighting of dynamic properties may be set to be greater than the weighting of static properties. This is because, in the initial stages of operation, the influence of factors such as operating speed may be small, and in such cases, the physical characteristics can be reproduced with high accuracy even if approximated by static characteristics. However, in the stages of operation where the change in operating reaction force in response to the movement associated with the operation becomes large, the influence of factors such as operating speed may be large, and in such cases, approximating with dynamic characteristics can reproduce the physical characteristics with greater accuracy. Furthermore, the correspondence information stored in the sensibility database 16 may include information that reflects the differences in the response characteristics of receptors mainly acting on touch, pressure, and force in the narrow sense. By generating the conversion model 15 based on such correspondence information, it becomes possible to present tactile sensations that more accurately reflect human sensibilities.

[0111] (Haptic control system 2) Figure 20 shows the configuration of the tactile control system 2, which is a second embodiment of the sensory control system 100 shown in Figure 1, along with the signal flow.

[0112] The haptic control system 2 shown in Figure 20 comprises a terminal device 80 and a communication device 70, which are connected to each other via a network 9 for communication. The terminal device 80 comprises a main control unit 6, an input / output device 3, and a haptic presentation device 20. The main control unit 6 comprises a processor 7 and a storage unit 8, and controls the operation of the input / output device 3 and the haptic presentation device 20. The haptic presentation device 20 comprises a haptic presentation unit 30, an operating range variable unit 29, and sensors such as a position sensor 27 and an acceleration sensor 28. The communication device 70 is, for example, a server device, and comprises a processor 14, a storage unit 11, an arithmetic function unit 12, and an arithmetic function unit 13. The storage unit 11 stores a conversion model 15.

[0113] Of the components of the haptic control system 2, the input / output device 3, the haptic presentation device 20, the processor 14, the storage unit 11, the arithmetic function unit 12, and the arithmetic function unit 13 are the same as the components of the haptic control system 1 shown in Figure 2, which are indicated by the same reference numerals, so their explanation is omitted. The terminal device 80 may also be equipped with an operating device 33, and the haptic presentation unit 30 may provide tactile feedback to the user operating the operating device 33, just as in the haptic control system 1. Furthermore, the haptic control system 2 may be equipped with a haptic presentation unit 43 shown in Figure 19 instead of the haptic presentation unit 30, and an operating device 42 shown in Figure 19 instead of the operating device 33.

[0114] Figure 21 is a sequence diagram showing the operation of the haptic control system 2. In Figure 21, the processes performed by the terminal device 80 and the communication device 70 of the haptic control system 2 are explained in steps (ST). First, in ST31, the terminal device 80 receives input of affective parameters. Specifically, the terminal device 80 receives affective parameters input by the user, etc., via the input section 4 of the input / output device 3. Next, in ST32, the terminal device 80 encodes the affective parameter information and transmits the encoded affective parameter information to the communication device 70 via the network 9. The terminal device 80 may be equipped with an encoder for encoding the affective parameter information. Also, the terminal device 80 may encode the entire affective parameter information or only a part of it.

[0115] After ST32, in ST21, the communication device 70 decodes the information received from the terminal device 80 to obtain information on the affection parameters. The communication device 70 may also be equipped with a decoder for decoding the information on the affection parameters. Next, in ST22, the communication device 70 uses the conversion model 15 to convert the affection parameters into physical parameters correlated with those affection parameters. Next, in ST23, the communication device 70 encodes the converted physical parameters and transmits the encoded information on the physical parameters to the terminal device 80 via the network 9. The communication device 70 may also be equipped with an encoder for encoding the information on the physical parameters. Furthermore, the communication device 70 may encode the entire information on the physical parameters or only a part of it.

[0116] After ST23, in ST33, the terminal device 80 decodes the received information to obtain physical parameter information. The terminal device 80 may also be equipped with a decoder for decoding the physical parameter information. Subsequently, in ST34, the terminal device 80 generates a haptic presentation signal based on the physical parameters and operates the haptic presentation device 20. Note that the encoding and decoding processes in ST32, ST21, ST23, and ST33 are not mandatory.

[0117] Thus, in this embodiment, when a tactile parameter is input to the terminal device 80, the tactile control system 2 receives information on physical parameters correlated with the tactile parameter from the communication device 70 via the network 9, and can then present tactile sensations using tactile presentation signals based on those physical parameters. Therefore, the tactile control system 2 enables the presentation of tactile sensations that reflect human sensibilities through the communication of tactile information via the network 9. The tactile control system 2 is particularly useful in the field of the Tactile Internet.

[0118] Furthermore, when communicating all physical parameters included in the physical characteristics related to tactile presentation, problems such as communication delays tend to occur due to the increase in data volume. However, in the tactile control system 2 according to this embodiment, physical parameters correlated with the affective parameters are extracted and communicated, thereby reducing the amount of data. Therefore, this can contribute to faster communication and reduced load on each processor, etc. This effect is also present in the tactile control system 1 according to the first embodiment, but it is particularly useful in the tactile control system 2 according to this embodiment, which uses a tactile internet.

[0119] The haptic control system 2 according to this embodiment may include a plurality of terminal devices 80. That is, the communication device 70 may be connected to each of the plurality of terminal devices 80 via a network 9. In that case, the communication device 70 may store identification information such as addresses or IDs that specify each of the plurality of terminal devices 80, and a conversion model 15 associated with each piece of identification information. This allows the conversion model 15 to be optimized and configured for each user using each terminal device 80.

[0120] Furthermore, the conversion models 15 stored in the communication device 70 of the haptic control system 2 according to this embodiment may be multiple, depending on the application (e.g., for games, for in-vehicle use), and different conversion models may be used depending on the application required by the terminal device 80. This allows the conversion models 15 to be optimized and configured according to the application, so that different physical parameters can be selected depending on the application, even if the physical parameters are converted from the same sensory parameters.

[0121] Although Figure 20 shows an example where the conversion model 15 is stored in the memory unit 11 of the communication device 70, the conversion model 15 may also be stored in the memory unit 8 of the main control unit 6 of the terminal device 80. In this case, for example, information regarding affective parameters (including encoded information, etc.) may be distributed from the communication device 70, and the main control unit 6 of the terminal device 80 may convert the affective parameters into physical parameters, thereby generating a tactile presentation signal based on physical parameters correlated with the affective parameters.

[0122] (Application examples of haptic control systems 1 and 2) The haptic control system 1 according to the first embodiment can be used for entertainment purposes such as games, videos, and music. When the haptic control system 1 is used for entertainment purposes, tactile feedback from the haptic presentation device 20 may be presented to the user through operating parts such as buttons, joysticks, and trigger switches included in an operating device 33, such as a game controller. Alternatively, tactile feedback from the haptic presentation device 20 may be presented to parts of the operating device 33 other than the operating parts, such as the user's hand holding the operating device 33, in whole or in part. The game controller may be, for example, a steering controller that mimics a car's steering wheel.

[0123] The timing for providing haptic feedback to the user through the operating device 33 includes the timing when an operation on the operating part included in the operating device 33 is detected, the timing when an operation such as movement, rotation, or acceleration / deceleration of the entire or a part of the operating device 33 is detected, and the timing for providing haptic feedback according to the content. The timing for providing haptic feedback according to the content may be a haptic feedback timing that is pre-set within each piece of content, such as games, videos, or music, for example, to enhance the sense of realism, and may be at a time when no user operation has been detected.

[0124] When the haptic control system 1 is used for entertainment purposes, haptic presentation from the haptic presentation device 20 is not limited to being performed through the operating device 33 described above. Haptic presentation from the haptic presentation device 20 may also be performed, for example, through a seat on which the user sits, a suit worn by the user, a headset used for virtual reality (VR) or augmented reality (AR) applications, gloves or other wearable devices worn by the user on body parts such as the hands, or other wearable devices. For example, the sensation of operating a virtual switch in a VR or AR space may be presented through a wearable device.

[0125] The haptic control system 1 according to the first embodiment can be used, for example, in an in-vehicle application. When used in an in-vehicle application, haptic presentations from the haptic presentation device 20 may be made to the occupant through devices used for driving operations such as the steering wheel, pedals, and shifter, or through operating devices 33 such as infotainment systems, air conditioning units, decorative panels, or seat cushions. Here, the decorative panel is provided at any location in the vehicle interior, such as the door trim, pillars, glove box, center console, dashboard, and overhead console, and constitutes the interior of the vehicle, and is a device that can display information through touch or proximity operation.

[0126] When the haptic control system 1 is used in an in-vehicle application, the main purpose of providing haptic feedback is to notify the occupants that an input operation has been performed on the control device 33, etc., and to warn them about lane departures, approaching other vehicles, etc. In other words, the purpose may differ from the aforementioned entertainment applications, which primarily aim to provide a sense of presence. For this reason, the haptic control system 1 may store conversion models 15 that can convert physical parameters, even if they are converted from the same sensory parameters, into different physical parameters depending on the application.

[0127] When the haptic control system 1 is used in an in-vehicle application, possible timings for providing haptic feedback to the occupant include the timing when an input operation to the control device 33 is detected, and the timing when a hazard such as lane departure or approaching another vehicle is detected.

[0128] The haptic control system 2 according to the second embodiment can be used for the same purposes as the haptic control system 1 according to the first embodiment. That is, the haptic control system 2 can be used, for example, for entertainment purposes such as games, videos, and music, and for in-vehicle applications.

[0129] When the haptic control system 2 according to the second embodiment is used for entertainment purposes, in addition to being used in the same way as the haptic control system 1 in Figure 1, haptic presentation signals may be sent, received, and distributed in conjunction with live content distribution (including broadcasting) via the network 9, content data updates, user interaction and competition, etc. For example, when the communication device 70 communicates with multiple terminal devices 80, a common sensitivity parameter may be set for each terminal device 80, or individual sensitivity parameters may be set for each terminal device 80, or some sensitivity parameters may be set in common for each terminal device 80 while other sensitivity parameters are set individually. For example, when having users of multiple terminal devices 80 work in a common VR or AR environment, the sensitivity parameter indicating the magnitude of the sensation may be common for each terminal device 80, while the sensitivity parameter indicating the sharpness of the sensation may be adjusted according to the user's preference for each terminal device 80, thereby individually adjusting the environment.

[0130] When the haptic control system 2 is used in an in-vehicle application, in addition to being used in the same way as the haptic control system 1, it may also receive haptic notification signals for warnings, etc., based on communication between vehicles via the network 9, communication with road installations such as traffic signs, and distribution of traffic information from a server. Communication between vehicles and communication with road installations can also be realized with the haptic control system 1 according to the first embodiment, if direct communication is possible without going through the network 9.

[0131] The haptic control system 2 according to the second embodiment can be used, for example, in medical or industrial applications. Medical applications include, for example, the transmission of haptic information associated with telemedicine. Industrial applications include, for example, the transmission of haptic feedback associated with the remote operation of industrial robots. If the haptic feedback transmitted in these applications can be customized based on sensory values, it will be possible to present a more realistic tactile sensation to the user and enable comfortable operation.

[0132] The haptic control system 2 according to the second embodiment can be used, for example, for internet shopping. For example, it can present the user with tactile sensations such as the feel of a product, how it feels to wear, or the writing feel through a writing instrument, via haptic transmission. Furthermore, it can customize the feel and fit of a product based on sensory values, and propose products to the user that are closer to the feel and fit they desire.

[0133] The haptic control system 2 according to the second embodiment can be used for communication between users in remote locations. It can provide users in remote locations with the sensation of shaking hands, touching, etc. It can also provide the sensation of touching an animal such as a pet. In these applications, using or combining a thermal sensation presentation as the haptic presentation unit 30 is particularly useful because it can convey warmth. [Aspect 2] [Background technology] Conventionally, there are known devices that provide sensory feedback by stimulating a person. Here, sensory feedback includes tactile feedback, auditory feedback through sound, and visual feedback through image display, etc. Sensory feedback is adjusted by adjusting the signals that drive various devices.

[0134] Technologies for producing products according to user preferences are known (see, for example, Patent Document 2). Patent Document 2 discloses a technology in which a user selects a standard model, and in subsequent processes, the color, size, material, position, etc., are added or modified based on the user's selection.

[0135] [Overview of the prefecture] [Problems the invention aims to solve] However, conventional technologies have a problem in that they cannot adjust sensory presentation through emotional input. In other words, while users have different preferences for sensations, they may express their preferences emotionally. However, conventionally, this emotional expression has not been used to modify sensory presentation.

[0136] In view of the above problems, the present invention aims to provide a tactile control device that can adjust the feel of operation through sensory input.

[0137] [Explanation of Embodiment 2] Embodiment 1 described a sensory control method that converts affective parameters to physical parameters using a conversion model 15. However, even if a manufacturer prototypes a control device in which the physical parameters converted from affective parameters are applied to tactile presentation, it is often necessary to go through several rounds of trial and error to obtain the user's preferred operating feel. Since prototyping a control device requires many steps, it can take time to complete a control device with the user's preferred operating feel.

[0138] Therefore, this embodiment describes a haptic control device that can reproduce the user's preferred operating feel in real time, and a haptic control method performed by the haptic control device.

[0139] [Examples of tactile control devices] Figure 25 is a perspective view of the tactile control device 50. Figure 25 shows a standalone tactile control device 50. As shown in Figure 25, the tactile control device 50 has three reference operating tools 51a to 51c (multiple reference operating tools), a reproduction operating tool 52, a touch panel 53, and a display 260. Hereafter, any of the reference operating tools 51a to 51c will be referred to as "reference operating tool 51". There may be two or more reference operating tools 51.

[0140] The display 260 shows instructions for using the haptic control device 50, operation menus, etc. The touch panel 53 displays emotional parameters (e.g., adjectives) for which expressiveness levels are entered, allowing the user to input expressiveness levels for each emotional parameter. When the haptic control device 50 reproduces the user's preferred tactile sensation, it accepts input of expressiveness levels for each emotional parameter multiple times, so the touch panel 53 displays the emotional parameters for which expressiveness levels can be entered each time.

[0141] The three standard operating tools 51a to 51c are operating tools with different operating sensations that were prepared as a standard. In other words, each of the three standard operating tools 51a to 51c has a different load displacement curve.

[0142] By inputting a preferred degree of expression, the reproduction control device 52 reproduces the feel of the reference control device 51 selected by the tactile control device 50 from among the three reference control devices 51a to 51c. In other words, the tactile control device 50 copies the physical parameters of one of the three reference control devices 51a to 51c to the reproduction control device 52. The user can then operate this reproduction control device 52 and input a degree of expression to adjust it to their preferred feel.

[0143] Therefore, the user can adjust the feel of the operation in real time by repeatedly operating the reproduction control device 52, checking its feel, inputting the degree of expression, and adjusting the feel of the reproduction control device 52. In addition, the user can compare the feel of the adjusted reproduction control device 52 with the feel of the reference control devices 51a to 51c, making it easier to adjust the degree of expression to their preference.

[0144] Note that the shape and appearance shown in Figure 25 are just examples; a general-purpose system configuration in which the reference operating device 51 and the reproduction operating device 52 are connected to a PC or tablet terminal via a USB cable or the like is also acceptable.

[0145] Figure 26 shows a client-server type haptic control system 2. In the haptic control system 2 of Figure 26, the terminal device 80 and the server 200 can communicate via a network. The terminal device 80 may run, for example, a web browser or a dedicated application. The terminal device 80 displays the necessary screen information for inputting the expression degree for each sensory parameter and accepts the expression degree input from the user. The terminal device 80 transmits the expression degree to the server 200, and the server 200 transmits the selection result of the reference operating tools 51a to 51c, the physical parameters corresponding to the reference operating tools 51a to 51c, and the adjusted physical parameters to the terminal device 80.

[0146] Thus, even with a client-server architecture, users can adjust the feel of the operation in real time, just like with the haptic control device 50.

[0147] <First form of tactile control device> First, the operation of the tactile control device 50 will be outlined with reference to Figures 27 and 28. Figures 27 and 28 show an outline of the process by which a user adjusts the feel of the controls using the tactile control device 50.

[0148] (1) The user first inputs a degree of expression (an example of the first degree of expression) that represents their preference for several emotional parameters (e.g., adjectives) (Figure 27(a)). The touch panel 53 displays the first input screen 281 shown in Figure 27(a), which has an emotional parameter display field 282 and a reference operating tool field 112. In the emotional parameter display field 282, the user can input the degree of expression for each emotional parameter (an example of the first emotional parameter) using a slider bar (an example of an input means). The reference operating tool field 112 displays the probability of selecting a reference operating tool 51a to 51c for the input degree of expression.

[0149] (2) The tactile control device 50 selects the reference operating device 51a to 51c that is closest to the user's preference (the inputted expression frequency of each sensory parameter) based on the correspondence between the expression frequency of each sensory parameter and the reference operating devices 51a to 51c, which have been learned in advance (Figure 27(b)). This process is called STEP 1.

[0150] (3) The tactile control device 50 reproduces the feel of operating the reference operating tools 51a to 51c using the reproduction operating tool 52 (Figure 27(c)). In Figure 27, there are three reference operating tools 51a to 51c, but this is just one example. The user tries operating the reproduction operating tool 52 to see if it has the feel they prefer.

[0151] (4) If the operating feel differs from the user's preference, the user re-enters expressive degrees (an example of second expressive degrees) that represent their preference for multiple sensory parameters (Figure 28(a)). The touch panel 53 displays the second input screen 120 shown in Figure 28(a), which has a sensory parameter display area 121. In the sensory parameter display area 121, the user can input expressive degrees for each sensory parameter (an example of second sensory parameters) using a slider bar. The number of sensory parameters in the sensory parameter display area 121 may be less than the number of sensory parameters in the sensory parameter display area 282. This is because the user's preferred standard operating tool 51 has already been selected in the sensory parameter display area 282. In addition, a smaller number of sensory parameters in the sensory parameter display area 121 reduces the user's workload.

[0152] In the initial state of the sensitivity parameter display area 121, the expression frequency of the slider bar shows the median value. Even if the user sets the expression frequency of the same sensitivity parameter to the minimum or maximum value in the sensitivity parameter display area 282, the expression frequency of the slider bar in the initial state of the sensitivity parameter display area 121 remains at the median value. This makes it easier for the user to adjust the expression frequency in the sensitivity parameter display area 121 to be within a range including the expression frequency entered in the sensitivity parameter display area 282. Furthermore, the expression frequency in the initial state of the sensitivity parameter display area 121 corresponds to the expression frequency of the physical parameter set in the reference control device 51. By adjusting from this initial state, the user can adjust to the expression frequency before or after the set value.

[0153] (5) The tactile control device 50 converts the expressive frequencies of each sensory parameter input by the user into physical parameters based on a pre-learned correspondence between the expressive frequencies of each sensory parameter and physical parameters (e.g., a regression model), and reflects this in the reproduction control device 52 (Figure 28(b)). This process is called STEP 2. (6) The user tries operating the replica operating device 52 to see if it has the feel they prefer (Figure 28(c)).

[0154] From this point onward, the user repeats steps (4) to (6), allowing the tactile control device 50 to determine the physical parameters of the user's preferred operating sensation.

[0155] [About the functions of the tactile control device] Figure 29 is a functional block diagram illustrating the functions of the tactile control device 50. As shown in Figure 29, the tactile control device 50 includes a display control unit 61, a first input receiving unit 62, a second input receiving unit 63, a classification unit 64, a first conversion model 65a, a second conversion model 65b, a third conversion model 65c, and a physical parameter setting unit 66. Each of these functions of the tactile control device 50 is realized by a CPU or processor, which is part of the information processing device, executing a program loaded into RAM. Alternatively, each function may be realized by hardware circuits.

[0156] The display control unit 61 displays preset emotional parameters and selectable levels of expression (5 or 7 levels) for each emotional parameter on the touch panel 53 (displaying the first input screen 281 and the second input screen 120). The level of expression can be adjusted in arbitrary steps or continuously. The user can select the level of expression by tapping on the touch panel 53 or by sliding a slider bar. The user can also select the level of expression by voice input or button input. The display control unit 61 displays different emotional parameters in STEP 1 and STEP 2. The number of emotional parameters in STEP 1 may be greater than the number of emotional parameters in STEP 2.

[0157] The first input receiving unit 62 accepts input of the expression degree of each emotional parameter in response to user operation in STEP 1. The second input receiving unit 63 accepts input of the expression degree of each emotional parameter in response to user operation in STEP 2.

[0158] The classification unit 64 is an identification model that has learned the correspondence between the expression frequencies of the affective parameters received by the first input receiving unit 62 and the three transformation models. There are many types of learning methods for classification, such as deep learning, decision trees, and support vector machines, but in this embodiment, any learning method may be used. The classification unit 64 outputs identification information for the first transformation model 65a to the third transformation model 65c in response to the expression frequencies of the affective parameters received by the first input receiving unit 62 (identifying the transformation model 15 that is closest to the user's preferences from among the multiple transformation models 15).

[0159] The first to third transformation models 65a to 65c are transformation models capable of converting sensory parameters into physical parameters correlated with those sensory parameters, as described in Embodiment 1. The first to third transformation models 65a to 65c correspond to three reference operating tools 51a to 51c, and the expressive frequency of sensory parameters can be converted into physical parameters for each of the reference operating tools 51a to 51c. Physical parameters include, for example, the stroke amount of the operating tool, the operating reaction force (load), the speed of the movable part, acceleration, jerk, and the elastic properties of body parts such as the operator's fingers. In order to reproduce different operating sensations, the first to third transformation models 65a to 65c are generated by multiple regression or the like based on the expressive frequency of sensory tests for different physical parameters of the load-displacement curves.

[0160] Then, the first conversion model 65a to the third conversion model 65c convert the expression degree of the affective parameter received by the second input receiving unit 63 into different physical parameters. In this way, the reference conversion model selected in STEP 1 can convert the expression degree that is close to the user's preferences entered in STEP 2 into physical parameters.

[0161] The physical parameter setting unit 66 sets the physical parameters output by any of the first conversion models 65a to the third conversion model 65c to the reproduction control device 52. Therefore, the tactile control device 50 can reproduce the operating sensation desired by the user in real time.

[0162] [Generation of the classification unit, learning the correspondence between the expressiveness of affective parameters and physical parameters] Next, the generation of the classification unit 64 will be explained with reference to Figure 30, etc. Figure 30 is a flowchart showing the learning process in the generation of the classification unit 64. Although the tactile control device 50 is assumed to perform various learning processes, any information processing device can perform the learning process.

[0163] In ST41, the tactile control device 50 accepts the expression frequency input. The affective parameters used for generating the classification unit 64 are shown in Figure 27(a). There are, for example, 24 affective parameters. 24 is just one example, and there may be fewer or more. "Light (heavy) operating force" "There is (or is) no sense of decisiveness" "Inaccurate (accurate)" "Clear (ambiguous)" "Soft (hard)" "blurred (clear)" "To get stuck (smoothly)" "Tired (Not tired)" "Strict (gentle)" "Rough (fine)" "There is (or is) a feeling of being sucked in." "Innovative (traditional)" "Cheap (high-end)" "Durable (or not)" "I don't want to operate it again (but I do)." "Fun (or boring)" "Not comfortable (or comfortable)" "I hate (I like)" "There is (or is) no bouncy feeling." "Mild (Sharp)" "Dry (wet)" "Bright (Dark)" "cold (warm)" "With (or without) playfulness" These sentiment parameters may be automatically generated through web analytics, tweet analytics, social media analytics, research papers, market-specific clustering analysis, and feature and adjective extraction. In other words, the sentiment parameters do not have to be fixed and may be dynamically changeable.

[0164] In ST42, the tactile control device 50 learns the correspondence between the expressiveness of the affective parameters and the reference operating tools 51a to 51c through machine learning. The classification unit 64 has this correspondence.

[0165] Machine learning is a technique for enabling computers to acquire human-like learning abilities. It involves computers autonomously generating algorithms necessary for data identification and other decision-making processes from pre-programmed training data, and then applying these algorithms to new data to make predictions. The learning method for machine learning can be supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, or deep learning, or a combination of these methods; the learning method itself is not limited. Furthermore, machine learning techniques include perceptrons, deep learning, support vector machines, logistic regression, naive Bayes, decision trees, and random forests, and the learning methods are not limited. Deep learning and decision trees will be explained later as examples of learning methods.

[0166] In ST43, the classification unit 64 generated by machine learning is incorporated into the tactile control device 50.

[0167] Figure 31 is a flowchart illustrating the learning process for the correspondence between the expressiveness of affective parameters and physical parameters.

[0168] In ST51, the tactile control device 50 accepts input of expression frequencies. The affective parameters used for learning the correspondence between the expression frequencies of the affective parameters and the physical parameters are shown in Figure 28(a). For example, there are five affective parameters. Five is just one example; there may be fewer or more. "Mild (Sharp)" "Rough (fine)" "(Bright (dark))" "(Soft (hard))" "(Light (heavy))" In ST52, the tactile control device 50 determines the correspondence between the expression frequency of the sensory parameter and the physical parameter by multiple regression analysis. In this aspect, since three reference operation tools 51a to 51c are prepared, a load-displacement curve is obtained for each of the three reference operation tools 51a to 51c. The physical parameters for realizing this load-displacement curve are also known. The user operates the reference operation tools 51a to 51c and inputs the expression frequency of what kind of operation feeling for these reference operation tools 51a to 51c. When the expression frequencies of a sufficient number of people are input, the tactile control device 50 performs multiple regression analysis using Equation 5. The multiple regression analysis was described in Equation 5 of Aspect 1, FIGS. 22 and 23. Therefore, the determination coefficients B 11 ~B mn for each of the three reference operation tools 51a to 51c can be determined, and a conversion model 15 as shown in FIG. 23 is obtained for each of the reference operation tools 51a to 51c. The conversion models for these three reference operation tools 51a to 51c are the first conversion model 65a to the third conversion model 65c.

[0169] In ST53, the first conversion model 65a to the third conversion model 65c generated by multiple regression analysis are incorporated into the tactile control device 50.

[0170] [Flow of Tactile Presentation] FIG. 32 is a flowchart showing the flow in which the tactile control device 50 presents the operation feeling preferred by the user using the classification unit 64 and the first conversion model 65a to the third conversion model 65c.

[0171] In ST61, the first input reception unit 62 selects the reference operation tools 51a to 51c and receives the input of the expression frequency of the sensory parameter on the first input screen 281 (STEP1).

[0172] In ST62, the classification unit 64 identifies the reference operating tools 51a to 51c based on the expression frequency of each emotional parameter entered on the first input screen 281. Once the reference operating tools 51a to 51c are determined, one of the conversion models from the first conversion model 65a to the third conversion model 65c is also determined.

[0173] In ST63, the physical parameter setting unit 66 sets the physical parameters of the selected reference operating tools 51a to 51c to the reproduction operating tool 52. The user can then operate the reproduction operating tool 52 to confirm whether the operating feel is to their liking.

[0174] In S64, the user decides whether to adjust the operating feel to a different one from the standard operating tools 51a to 51c, depending on whether the operating feel is to their liking. The tactile control device 50 receives a command from the user to start readjustment.

[0175] In S65, when the user adjusts the operating feel to be different from that of the standard operating tools 51a to 51c, the second input receiving unit 63 accepts the input of the expression degree of the sensibility parameter on the second input screen 120 (STEP 2). The expression degree entered by the user (A1 to A in Figure 23) n (This corresponds to) any of the first transformation models 65a to third transformation models 65c selected in ST63 is physical parameter P1 to P n Convert to this. The physical parameter setting unit 66 converts these physical parameters P1~P n The setting is then applied to the reproduction control device 52. The user can then operate the reproduction control device 52 again to confirm whether the operating feel is to their liking.

[0176] From this point onward, the user can repeatedly adjust the control feel using the second input screen 120 until they achieve their preferred control feel.

[0177] Thus, the tactile control device 50 of this embodiment can reproduce the user's preferred operating sensation in real time.

[0178] <Second form of tactile control device> Next, we will describe the second form of the tactile control device 50.

[0179] First, with reference to Figure 33, the operation of the second form of the tactile control device 50 will be outlined. Figure 33 shows an outline of the process by which a user adjusts the feel of the controls using the tactile control device 50.

[0180] (1) First, the user inputs the degree of expression representing their preferences for several sensibility parameters on the first input screen 281 (Figure 33(a)). The first input screen 281 can be the same as in Figure 27(a).

[0181] (2) The tactile control device 50 determines a physical parameter (an example of a second physical parameter) corresponding to the expressive frequency of each sensory parameter (an example of a second physical parameter) based on the correspondence between the expressive frequency of each sensory parameter and the physical parameter (load displacement curve), which has been learned in advance by regression (Figure 33(b)).

[0182] (3) The tactile control device 50 performs curve fitting on the load-displacement curves of the pre-prepared reference operating tools 51a to 51c using an appropriate fitting model (Figure 33(c)). This fitting model is, for example, a polynomial with physical parameters as coefficients. Therefore, physical parameters representing the load-displacement curve (an example of the first physical parameters) are obtained for each reference operating tool 51a to 51c. The tactile control device 50 compares the physical parameters in (2) with the physical parameters in (3).

[0183] (4) If the physical parameters in (2) and the physical parameters in (3) are similar, the tactile control device 50 will present a similar reference operating tool 51; otherwise, it will suggest adjusting the new sensation using the reproduction operating tool 52 (Figure 33(d)).

[0184] [About the functions of the tactile control device] Figure 34 is a functional block diagram illustrating the functions of the tactile control device 50. Note that the explanation of Figure 34 may primarily focus on the differences from Figure 29. The tactile control device 50 includes a display control unit 61, a first input receiving unit 62, a second input receiving unit 63, a physical parameter conversion unit 67, a curve fitting unit 68, a comparison unit 69, a first conversion model 65a, a second conversion model 65b, a third conversion model 65c, and a physical parameter setting unit 66. Each of these functions of the tactile control device 50 is realized by the CPU, which functions as an information processing device, executing a program loaded into RAM. Alternatively, each function may be realized by hardware circuits.

[0185] The physical parameter conversion unit 67 uses the correspondence between the expression frequencies obtained by the multiple regression analysis and the physical parameters to determine the physical parameters for the expression frequencies received by the first input receiving unit 62. Since determining the physical parameters also determines the load-displacement curve, it can be said that the physical parameter conversion unit 67 determines the load-displacement curve.

[0186] The curve fitting unit 68 fits the load-displacement curves of the reference operating devices 51a to 51c (first transformation model 65a to third transformation model 65c) using an appropriate fitting model (e.g., a polynomial). Curve fitting is a form of multiple regression analysis. By setting physical parameters as coefficients in the polynomial, the curve fitting unit 68 can estimate the physical parameters for each of the reference operating devices 51a to 51c. Therefore, the fitting model should be selected so that the load-displacement curves can be fitted using physical parameters.

[0187] The comparison unit 69 compares the physical parameters determined by the physical parameter conversion unit 67 with the physical parameters determined by the curve fitting unit 68 and determines whether they are similar or not. For example, the comparison unit 69 compares physical parameters P1 to P n The sum of the squares of the differences is calculated for each, and it is determined whether or not it is below a threshold. If there are similar physical parameters, the comparison unit 69 instructs the physical parameter setting unit 66 to set the physical parameters corresponding to the reference operating tools 51a to 51c.

[0188] The physical parameter setting unit 66 sets the physical parameters of the specified reference operating tool 51 to the reproduction operating tool 52.

[0189] [Learning physical parameters (load-displacement curves) corresponding to the frequency of expression, and curve fitting of the load-displacement curve of the reference operating device] Next, we will explain the learning of physical parameters (load-displacement curves) corresponding to the expressive frequency, referring to Figure 35, etc. Figure 35 is a flowchart showing the flow of learning physical parameters (load-displacement curves) corresponding to the expressive frequency.

[0190] In ST71, the tactile control device 50 accepts input of expression frequency. The affective parameters used for generating the classification unit 64 are shown in Figure 27(a).

[0191] In ST72, the tactile control device 50 determines the correspondence between the expressive frequencies of the affective parameters and the physical parameters using multiple regression analysis. For an operating tool with known physical parameters, the user inputs the expressive frequency of how it feels to operate. The operating tool with known physical parameters may be the reference operating tool 51 or any other operating tool. Once a sufficient number of expressive frequencies have been input, the tactile control device 50 performs multiple regression analysis using Equation 5. Multiple regression analysis is explained in Equation 5, Figures 22 and 23 of Embodiment 1. Therefore, the tactile control device 50 determines the coefficient of determination B of Equation 5. 11 ~B mn This allows us to determine the conversion model 15 shown in Figure 23.

[0192] In ST73, the physical parameter conversion unit 67 generated by multiple regression analysis is incorporated into the tactile control device 50.

[0193] Figure 36 is a flowchart illustrating the process of curve fitting the load-displacement curves of the reference operating devices 51a to 51c.

[0194] In ST81, the curve fitting section 68 performs curve fitting to the load-displacement curves of the reference operating tools 51a to 51c. As shown in Figure 9, a correspondence between stroke amount x and operating reaction force is obtained for each of the reference operating tools 51a to 51c. The curve fitting section 68 extracts pairs of stroke amount and operating reaction force from x=0 to the maximum stroke amount, preferably at regular intervals. The curve fitting section 68 applies the pairs of stroke amount x and operating reaction force y to a fitting model and performs curve fitting. The fitting model is an equation that determines the operating stress from the stroke amount x using physical parameters as coefficients. The fitting model below is just one example, and any appropriate model (equation) that determines the operating reaction force y from the stroke amount x using physical parameters as coefficients may be adopted. Fitting model: y = P1 × x 0 +P2×x 1 +P3×x 2 +......P n ×x n The curve fitting section 68 can determine P1 to Pn by multiple regression analysis. n These correspond to physical parameters.

[0195] In ST82, the physical parameters of each reference operating instrument 51a to 51c, generated by curve fitting, are set in the comparison unit 69.

[0196] [Flow of tactile presentation] Figure 37 is a flowchart illustrating the process by which the tactile control device 50 uses the physical parameter conversion unit 67 and the comparison unit 69 to present the user with a preferred operating sensation.

[0197] In ST91, the first input receiving unit 62 receives input of the expression degree of the affective parameter for selecting the reference operating tools 51a to 51c.

[0198] In ST92, the physical parameter conversion unit 67 converts each sensory parameter into physical parameters (load-displacement curves) based on its expressiveness.

[0199] In ST93, the comparison unit 69 compares the physical parameters determined by the physical parameter conversion unit 67 with the physical parameters for each of the reference operation tools 51a to 51c determined by the curve fitting unit 68.

[0200] In S94, the comparison unit 69 determines whether there are reference operation tools 51a to 51c having physical parameters similar to the physical parameters converted by the physical parameter conversion unit 67. The determination here is, as described above, based on whether the sum of the squares of the differences between the physical parameters P1 to P determined by the physical parameter conversion unit 67 n and the physical parameters P1 to P obtained by curve fitting of the reference operation tools 51a to 51c is less than the threshold value. n There is a method for making this determination.

[0201] If the determination in S94 is Yes, in S95, the physical parameter setting unit 66 sets the physical parameters of the reference operation tools 51a to 51c similar to the physical parameters determined by the physical parameter conversion unit 67 in the reproduction operation tool 52.

[0202] If the determination in S94 is No, in S96, the physical parameter setting unit 66 sets the physical parameters of the reference operation tool having the highest similarity among 51a to 51c in the reproduction operation tool 52. Alternatively, a classification unit 64 of the first form may be provided, and the classification unit 64 may determine the reference operation tools 51a to 51c (the first conversion model 65a to the third conversion model 65c).

[0203] Thereafter, until the user obtains the operation feeling they prefer, the user can repeatedly adjust the preferred operation feeling using the second input screen 120.

[0204] Thus, the tactile control device 50 of this aspect can reproduce the operation feeling preferred by the user in real time.

[0205] [Learning Example of Classification] Referring to FIG. 38 and the like, a classification learning method will be described. FIG. 38 shows an example of a neural network when the classification unit 64 is realized by a neural network. For the data input to the input layer 131 of the neural network in FIG. 38, three nodes in the output layer 133 each output an output value yi. This output value yi is a probability, and y1 + y2 + y3 = 1.0. In this embodiment, the three nodes in the output layer 133 correspond to the three reference operation tools 51a to 51c, and output the probability of which of the three reference operation tools 51a to 51c is likely according to the expression frequency.

[0206] FIG. 38 is a neural network in which L layers (for example, three layers) from the input layer 131 to the output layer 133 are fully connected. A neural network with a deep hierarchy is called a DNN (Deep Neural Network). The layer between the input layer 131 and the output layer 133 is called the intermediate layer 132. Since the number of layers and nodes in the intermediate layer can be arbitrarily set, the number of layers and the number of nodes 130 in each layer are merely examples. In this embodiment, the number of nodes 130 in the input layer is the number of sensory parameters (24 in FIG. 27(a)). Note that the expression frequency may be set with arbitrary gradation adjustment such as five gradations or three gradations for each sensory parameter, or may be continuously adjustable.

[0207] In a neural network, all nodes 130 in the l-1 layer (l (lambda): 2, 3) except the input layer are connected to one node 130 in the lth layer, and the product of the output z of the node 130 in the l-1 layer and the coupling weight w is input to the node in the lth layer. Equation (1) shows a method for calculating the output signal of the node 130.

[0208]

Equation

[0209]

number

[0210] Each node in the output layer 133 receives the z output from each node in the hidden layer 132. i The input is z, and each node in the output layer 133 is z i The values ​​are summed up. Then, the nodes of the output layer 133 use the activation function for the output layer. In the case of multi-class classification (selection of reference manipulators 51a to 51c), the activation function of the output layer 133 is generally the softmax function. Each node of the output layer 133 is the output value y of the softmax function. i The output is generated. During training, each node in the output layer 133 is associated with a reference control device, and a teacher signal (1 or 0) is set. If training is performed properly, each node in the output layer 133 can output the probability of the reference control devices 51a to 51c that correspond to the 24 affect parameters. In the figure, the nodes are shown from top to bottom as corresponding to the reference control devices 51a to 51c. However, if the output value is below the threshold, it may be judged as unclassified.

[0211] This section explains the training of a neural network. Multiple users operate three reference control devices 51a to 51c, inputting expression frequencies for each device. In this way, training data consisting of 24 affective parameters and one training signal (which reference control device) is obtained, in quantities equal to the number of users × the number of reference control devices. The training signal is one of (1,0,0), (0,1,0), or (0,0,1).

[0212] The neural network processes the expression frequencies input to the input layer 131 and outputs an output value yi from the output layer 133. The nodes of the output layer 133 receive the training signal, which is a pair of the input expression frequencies. During training, the error between the output value yi of the nodes in the output layer 133 and the training signal is calculated by the loss function. If the activation function of the output layer 133 is the softmax function, the loss function is cross-entropy. The error between the training signal and the output value calculated by the loss function is propagated to the nodes of the input layer 131 using a calculation method called backpropagation. The weights w between nodes are learned during the propagation process. Details of backpropagation are omitted.

[0213] As a result of the learning process, the neural network is expected to output a value close to 1.0 for the expression frequency input for, for example, the reference control device 51a, while the nodes 130 corresponding to the reference control device 51b and 51c output a value close to 0.0.

[0214] Note that although the nodes are fully connected in Figure 38, convolutional layers, pooling layers, etc., may be included.

[0215] Figure 39 shows an example of a decision tree when the classification unit 64 is implemented using a decision tree. A decision tree is a machine learning method that finds data clusters in which specific features frequently appear and generates classification rules for them. In this embodiment, learning involves determining the affective parameters that frequently appear for each of the three reference manipulation tools 51a to 51c and their expression frequencies. One known method for learning the structure of a decision tree is to use entropy.

[0216] In addition to neural networks and decision trees, other suitable machine learning methods for classification include support vector machines, random forests, and logistic regression.

[0217] [Supplementary information on the first input screen] Figure 40 is a diagram illustrating the first input screen 281 for the expression frequency in STEP 1. The user inputs the expression frequency by operating a slider bar for each emotional parameter. The classification unit 64, as described in the first form, uses the learning results to calculate the probability that each reference control device 51a to 51c is selected for the current expression frequency. The display control unit 61 displays the probability for each reference control device 51a to 51c in the reference control device column 112. Therefore, the user can determine which reference control device 51a to 51c is closest to the current expression frequency by operating the reference control devices 51a to 51c. The probability may be displayed in real time or depending on whether the user has entered a decision operation.

[0218] Furthermore, when the user presses the icons for the reference controls 51a to 51c in the reference control panel 112, the display control unit 61 initializes the slider bar in the sensory parameter display panel 282 to the expression frequency set for the reference controls 51a to 51c. Therefore, the user can easily check the expression frequency for each reference control control 51a to 51c. Note that the expression frequency at the time of initialization may be, for example, the median or average value of the expression frequencies entered for the reference control control 51 in the sensory test.

[0219] [Client-server system operation] Next, the operation of the client-server system will be explained with reference to Figure 41, etc. Figure 41 is a functional block diagram of the haptic control system 2 in which the first form of the haptic control device 50 is applied to the client-server system. In explaining Figure 41, the differences from Figure 29 will be mainly explained. As shown in Figure 41, the terminal device 80 and the server 200 have the same functions as the haptic control device 50 in Figure 29, except that the terminal device 80 and the server 200 each have a first communication unit 71 and a second communication unit 72.

[0220] FIG. 42 is a sequence diagram for explaining the operation of the tactile control system 2. In the description of FIG. 42, the differences from FIG. 32 will be mainly described.

[0221] In ST101, the first input receiving unit 62 receives an input of the expression frequency of the sensory parameters for selecting the reference operation tools 51a to 51c input to the first input screen 281 (STEP1).

[0222] In ST102, the first communication unit 71 of the terminal device 80 transmits the expression frequency of each sensory parameter to the server 200.

[0223] In ST103, the classification unit 64 of the server 200 selects the reference operation tools 51a to 51c based on the expression frequency of each sensory parameter.

[0224] In ST104, the second communication unit 72 of the server 200 transmits the physical parameters of the reference operation tools 51a to 51c to the terminal device 80. The first communication unit 71 of the terminal device 80 receives the physical parameters of the reference operation tools 51a to 51c, and the physical parameter setting unit 66 sets them to the reproduction operation tool 52.

[0225] In ST105, it is determined whether the user adjusts to an operation feeling different from the reference operation tools 51a to 51c according to whether it is the operation feeling the user prefers. When the user adjusts to an operation feeling different from the reference operation tools 51a to 51c, the second input receiving unit 63 receives an input of the expression frequency of the sensory parameters input on the second input screen 120 (STEP2).

[0226] In ST106, the first communication unit 71 of the terminal device 80 transmits the expression frequency of the sensory parameter to the server 200. <0\000977>

[0227] In ST107, any one of the first conversion model 65a to the third conversion model 65c (selected in ST103) of the server 200 converts the expression frequency into the physical parameters P1 to P n to.

[0228] In ST108, the physical parameter setting unit 66 of the server 200 transmits the converted physical parameters to the terminal device 80 via the second communication unit 72. The first communication unit 71 of the terminal device 80 sets the physical parameters of the reference operating tools 51a to 51c received by the reproduction operating tool 52.

[0229] Thus, the haptic control system 2 of this embodiment can reproduce the user's preferred operating feel in real time, even in a client-server system.

[0230] Figure 43 is a functional block diagram of the haptic control system 2 in which the second form of the haptic control device 50 is applied to a client-server system. The explanation of Figure 43 will mainly focus on the differences from Figure 34. As shown in Figure 43, the terminal device 80 and the server 200 have the same functions as the haptic control device 50 in Figure 34, except that the terminal device 80 and the server 200 each have a first communication unit 71 and a second communication unit 72, respectively.

[0231] Figure 44 is a sequence diagram illustrating the operation of the second form of the tactile control system 2. The explanation of Figure 44 mainly focuses on the differences from Figure 37.

[0232] In ST111, the first input receiving unit 62 receives input of the degree of expression of the sensibility parameter on the first input screen 281.

[0233] In ST112, the first communication unit 71 of the terminal device 80 transmits the expression degree of each emotional parameter to the server 200.

[0234] In ST113, the physical parameter conversion unit 67 of the server 200 converts each sensory parameter into physical parameters (load-displacement curves) based on its expressiveness.

[0235] In ST114, the comparison unit 69 of the server 200 compares the physical parameters converted by the physical parameter conversion unit 67 with the physical parameters for each of the reference operating tools 51a to 51c predetermined by the curve fitting unit 68.

[0236] In ST115, if there are reference operating tools 51a to 51c with similar physical parameters to the physical parameters determined by the physical parameter conversion unit 67, the second communication unit 72 transmits the physical parameters of one of the similar reference operating tools 51a to 51c to the terminal device 80. The first communication unit 71 of the terminal device 80 receives the physical parameters of the reference operating tools 51a to 51c, and the physical parameter setting unit 66 sets them in the reproduction operating tool 52.

[0237] In ST116, if there are no reference operating tools 51a to 51c with similar physical parameters to the physical parameters determined by the physical parameter conversion unit 67, the second communication unit 72 transmits the physical parameters of one of the reference operating tools 51a to 51c with the highest degree of similarity to the terminal device 80. The first communication unit 71 of the terminal device 80 receives the physical parameters of the reference operating tools 51a to 51c, and the physical parameter setting unit 66 sets them in the reproduction operating tool 52. Alternatively, a classification unit 64 of the first form may be provided, and the classification unit 64 may determine the reference operating tools 51a to 51c (first conversion model 65a to third conversion model 65c).

[0238] Thus, the haptic control system 2 of this embodiment can reproduce the user's preferred operating feel in real time, even in a client-server system.

[0239] [Additional information for aspect 2] [Claim 1] A tactile control device that controls the feel of operating a tool, A display control unit that displays an input means for a first expression frequency associated with a first emotional parameter, A first input receiving unit that receives input of the first expression frequency in response to user operation, It includes a physical parameter setting unit that sets pre-prepared physical parameters on a reproduction device based on the first expression frequency, The display control unit displays an input means for a second expression frequency associated with a second emotional parameter. A second input receiving unit that receives input of the second expression frequency in response to user operation, It includes a conversion unit that converts the second expression frequency into physical parameters using a regression model, The tactile control device is characterized in that the physical parameter setting unit sets the physical parameters converted by the conversion unit to the reproduction control device. [Claim 2] The classification unit has a first expression frequency that classifies the expression frequency into one of a plurality of reference operating devices, The tactile control device according to claim 1, characterized in that the physical parameter setting unit sets the physical parameters set in the reference operating device classified by the classification unit to the reproduction operating device. [Claim 3] A curve fitting unit performs curve fitting on load-displacement curves realized by a first physical parameter possessed by multiple reference operating tools, and estimates the first physical parameter for each of the multiple reference operating tools. It includes a physical parameter conversion unit that converts the first expression frequency into a second physical parameter using a regression model, The tactile control device according to claim 1, characterized in that the physical parameter setting unit sets the first physical parameter of the reference operating tool, which has the first physical parameter most similar to the second physical parameter, to the reproduction operating tool. [Claim 4] The tactile control device according to claim 2, characterized in that the second expression frequency input means can take the expression frequency corresponding to the physical parameter set for the reference operating tool classified by the classification unit, and the values ​​immediately before and after it. [Claim 5] The tactile control device according to claim 1, characterized in that the first tactile parameter and the second tactile parameter are each multiple, and the number of the first tactile parameters is greater than the number of the second tactile parameters. [Claim 6] The tactile control device according to claim 2, characterized in that the classification unit is generated by learning the correspondence between the operating feel of the plurality of reference operating tools and the expression frequency input for each of the first sensory parameters by the user operating each of the plurality of reference operating tools. [Claim 7] The tactile control device according to claim 2, characterized in that the regression model is generated by performing a regression analysis on the correspondence between the physical parameters of the plurality of reference operating tools and the expression frequencies input by the user for each of the second sensory parameters when the plurality of reference operating tools are operated. [Claim 8] The tactile control device according to claim 3, characterized in that the regression model is generated by performing a regression analysis on the correspondence between the physical parameters of an arbitrary reference operating tool and the expression frequency input for each of the first sensory parameters by operating the arbitrary reference operating tool. [Claim 9] The tactile control device according to claim 3, characterized in that the curve fitting section performs curve fitting on the load-displacement curve using a fitting model that determines the operating stress from the stroke amount using the first physical parameter as a coefficient, and estimates the first physical parameter. [Claim 10] The first and second sensibility parameters are adjectives. The tactile control device according to claim 1, characterized in that the first expression frequency and the second expression frequency are values ​​indicating the degree of the adjective. [Claim 11] The tactile control device according to any one of claims 1 to 10, characterized in that the first expression frequency and the second expression frequency are tactile information obtained when the user operates the control device, respectively. [Claim 12] The tactile control device according to claim 11, wherein in the regression model, the first expression frequency and the second expression frequency are correlated with the tactile operating force obtained when the operating tool is operated, respectively. [Claim 13] A tactile control device that controls the feel of operating a tool, A display control unit that displays an input means for a first expression frequency associated with a first emotional parameter, A first input receiving unit that receives input of the first expression frequency in response to user operation, Based on the aforementioned first expression frequency, it functions as a physical parameter setting unit that sets pre-prepared physical parameters to the reproduction control device. The display control unit displays an input means for a second expression frequency associated with a second emotional parameter. Furthermore, a second input receiving unit that accepts the input of the second expression frequency in response to user operation, This unit functions as a conversion unit that converts the aforementioned second expression frequency into physical parameters using a regression model. The program is characterized in that the physical parameter setting unit sets the physical parameters converted by the conversion unit to the reproduction operation device. [Claim 14] A tactile control device that controls the feel of operating a tool, and a tactile control method that controls touch, A step of displaying an input means for a first expression frequency associated with a first sensibility parameter, A step of receiving input of the first expression frequency in response to user operation, The steps include setting pre-prepared physical parameters on the reproduction device based on the aforementioned first degree of expression, A step of displaying an input means for a second expression frequency associated with a second sensitivity parameter, A step of receiving input for the second degree of expression in response to user operation, The steps include converting the second expression frequency into physical parameters using a regression model, The steps include setting the converted physical parameters in the reproduction device, A tactile control method characterized by having the following features. [Claim 15] A haptic control system in which terminal devices and servers communicate via a network, The aforementioned terminal device is A display control unit that displays an input means for a first expression frequency associated with a first emotional parameter, A first input receiving unit that receives input of the first expression frequency in response to user operation, A first communication unit that transmits the first expression frequency to the server, It includes a physical parameter setting unit that sets physical parameters transmitted from the server into a reproduction control device, The display control unit displays an input means for a second expression frequency associated with a second emotional parameter. It includes a second input receiving unit that receives input of the second expression frequency in response to user operation, The first communication unit transmits the second expression frequency to the server. The aforementioned server, A second communication unit determines the pre-prepared physical parameters based on the first expression frequency received from the terminal device and transmits the determined physical parameters to the terminal device. The device includes a conversion unit that converts the second expression frequency received from the terminal device into physical parameters using a regression model, The haptic control system is characterized in that the second communication unit transmits the physical parameters converted by the conversion unit to the terminal device. [Claim 16] A display control unit that displays an input means for a first expression frequency associated with a first emotional parameter, A first input receiving unit that receives input of the first expression frequency in response to user operation, The device includes a first communication unit that transmits the first expression frequency to a server, and a physical parameter setting unit that sets the physical parameters transmitted from the server into a reproduction control device. The display control unit displays an input means for a second expression frequency associated with a second emotional parameter. A server having a second input receiving unit that receives input of the second expression frequency in response to user operation, and a first communication unit that communicates via a network with a terminal device that transmits the second expression frequency to the server, A second communication unit determines pre-prepared physical parameters based on the first expression frequency received from the terminal device and transmits the determined physical parameters to the terminal device. The device includes a conversion unit that converts the second expression frequency received from the terminal device into the physical parameters using a regression model, The server is characterized in that the second communication unit transmits the physical parameters converted by the conversion unit to the terminal device. [Aspect 3] [Background technology] Conventionally, control units that provide sensory feedback by stimulating a person are known. Here, sensory feedback includes tactile feedback, auditory feedback through sound, and visual feedback through image display, etc. Sensory feedback is adjusted by adjusting the signals that drive various control units.

[0240] Game controllers with interchangeable buttons and other components that incorporate vibration devices are known (see, for example, Patent Document 3). Patent Document 3 discloses a technique for replacing the vibration device itself to achieve different vibration intensities.

[0241] [Overview of the prefecture] [Problems the invention aims to solve] However, conventional technology has a problem in that it does not adequately provide sensory feedback that corresponds to the physical characteristics of the control unit. For example, in the case of a rotary control unit, the size and mass of the control unit can affect the sensation transmitted to the user operating the unit, even if the actuator is driven in the same way.

[0242] In view of the above-mentioned problems, this embodiment aims to provide a technology that provides sensory feedback in accordance with the physical characteristics of the operating unit.

[0243] [Effects of the invention] We can provide technology that offers sensory feedback tailored to the physical characteristics of the control unit.

[0244] [Description of Embodiment 3] This embodiment describes a sensory control method that performs adjustments based on the physical characteristics of the operating unit (for example, the operating device 33 in Figure 45, which will be described later). When the haptic presentation device 20 generates tactile sensations through the operating unit driven by an actuator, depending on the physical characteristics of the operating unit (size, mass, etc.), even if the actuator is driven in the same way, the sensation transmitted to the user operating the operating unit (an example of an operator) (the operating sensation perceived by the user) may differ.

[0245] In other words, the physical parameters that correlate with the sensory parameters are composed of a combination of the physical parameters of the operating unit and the physical parameters of the actuator. Therefore, the tactile presentation device 20 in this embodiment is adjusted to produce a tactile presentation signal suitable for the physical parameters of the operating unit, such as the size and mass. The tactile control system 110 includes an adjustment unit that adjusts at least one of the operation signal, sensory presentation signal, or sensory presentation based on the physical characteristics of the operating unit.

[0246] For example, differences in the physical characteristics of the control unit can be detected as follows. The user inputs information about the differences in the physical characteristics of the control unit into the input / output device 3. The size and mass of the control unit are then determined. The tactile presentation device 20 uses sensors to detect differences in the physical characteristics of the operating part, such as ID, size, and mass. The sensor that detects differences in the physical characteristics of the control unit is a camera, which reads one-dimensional and two-dimensional codes. The camera also identifies the control unit by recognizing its image. Alternatively, the sensor is an IC tag reader, which reads the ID.

[0247] [Haptic control system 110] Figure 45 shows the configuration of the tactile control system 110 of the sensory control system 100 in this embodiment. In this embodiment, components that are denoted by the same reference numerals as in Figure 2 perform similar functions, so in some cases, only the main components of this embodiment may be described.

[0248] The tactile presentation device 20 in Figure 45 newly includes an operation unit sensor 254, a torque sensor 251, and a communication unit 256. The operation unit sensor 254 detects when a detachable operation unit is attached to the tactile presentation device 20, and also detects information that can identify the operation unit. Information that can identify the operation unit includes an IC tag built into the operation unit, a one-dimensional code or two-dimensional code attached to the operation unit, and the appearance of the operation unit. If the information that can identify the operation unit is an IC tag, the operation unit sensor 254 is an IC tag reader and obtains the ID (identification information) of the operation unit from the IC tag. If the information that can identify the operation unit is a one-dimensional code or two-dimensional code, the operation unit sensor 254 is a camera and obtains the ID of the operation unit from the one-dimensional code or two-dimensional code. If the information that can identify the operation unit is the appearance of the operation unit, the operation unit sensor 254 is a camera and a classifier and identifies the operation unit using a classifier that has learned the correspondence between image data of the appearance of the operation unit and its ID (the ID of the operation unit is known).

[0249] The operating unit is an example of an operating device 33, and the operating unit may be a detachable attachment part from at least a part (or the whole) of the operating device 33. The main control device 10 and the tactile presentation device 20 are examples of sensory control devices.

[0250] The torque sensor converts the current driving the actuator into torque during calibration to estimate the mass of the operating part. Further details will be described later.

[0251] The communication unit 256 communicates with the mobile terminal 60 to receive information about the size of the control panel from the mobile terminal 60. Further details will be described later.

[0252] Furthermore, the main control device 10 shown in Figure 45 newly includes an operation unit parameter 54, a calibration unit 55, and a mass correction unit 261. The operation unit parameter 54 will be explained in Figure 46. The calibration unit 55 estimates the mass of the operation unit through calibration. The mass correction unit 261 corrects the mass of the operation unit. The calibration unit 55 and the mass correction unit 261 will be described later.

[0253] Figure 46 shows an example of the control unit parameters 54. The control unit parameters 54 associate the control unit ID with mass, size, and other physical parameters. Mass and size are physical characteristics of the control unit 201, and in this embodiment, mass and size are included in the physical parameters.

[0254] For rotary-type operating parts that accept rotational operation, the size can be the radius, diameter, or overall length (length of the widest part). For push-type operating parts, the size can be the length in the pushing direction. For slide operating parts that accept sliding operation, the size can be the slide amount, height, width, or thickness. For pivot operating parts that accept tilting operation, the size can be the length of the operating part.

[0255] Other physical parameters are described in Embodiment 1. As shown in Figure 46, when the ID of the operating unit is detected by the operating unit sensor 254, the physical parameters can be determined. [Detection of the control unit by the control unit sensor] Referring to Figures 47 and 48, the method of detecting the operating unit by the operating unit sensor 254 will be explained. First, Figure 47 is a diagram illustrating the differences in the physical characteristics of rotary operating units. Figure 47(a) shows the small operating unit 201a, and Figure 47(b) shows the large operating unit 201b. In the following, any of the operating units 201a and 201b will be referred to as "operating unit 201".

[0256] The operating units 201a and 201b in Figure 47 are rotary type, but the tactile sensation transmitted to the user operating the operating unit will differ depending on the size (diameter) and mass of the operating units 201a and 201b, even if the processor 14 drives the actuators in the same way. For example, the torque required to rotate the operating unit 201 is smaller the larger the diameter. Therefore, if the reaction force for the rotational operation of operating units 201a and 201b is the same, the user may feel that it is difficult to turn operating unit 201a, or that there is no tactile sensation when operating unit 201b.

[0257] Even if the size of the control unit 201 differs, each control unit is usually similar in shape, so there is a certain relationship between size and mass. For example, there is a relationship where mass is proportional to the cube of the size (e.g., radius), and an approximate constant of proportionality can also be calculated. Therefore, as will be described later, it is possible to determine the mass from the size of the control unit 201, or the size from the mass, using a conversion formula.

[0258] Figure 48 illustrates several methods for detecting the size and mass of the control unit 201 using the control unit sensor 254. In Figure 48(a), the control unit 201 has an IC tag 202 built in or attached to it. In this case, the control unit sensor 254 is an IC tag reader 204, which uses electromagnetic waves to electrify the IC tag 202, communicates with the IC tag 202, and receives the ID of the control unit from the IC tag 202. The IC tag reader 204 is preferably installed in the tactile presentation device 20, but it may also be an external device such as a mobile terminal 60.

[0259] In Figure 48(b), a barcode 203 is attached to the control unit 201. In this case, the control unit sensor 254 captures the barcode 203 with the camera 205 and decodes the barcode 203 to obtain the ID of the control unit. The camera 205 is preferably installed in the tactile presentation device 20, but it may also be an external device such as a mobile terminal 60.

[0260] In Figure 48(c), the control unit sensor 254 photographs the control unit 201 itself with a camera. Based on the pre-set distance between the camera 205 and the control unit 201, and the focal length of the camera 205, the control unit sensor 254 estimates the size of the control unit sensor 254 from the image data. If the classifier has learned the correspondence between distance, focal length, image data of the control unit's appearance, and ID, it can output the ID of the control unit from the image data. For mass, a conversion formula is used to determine the mass from the size.

[0261] The operation unit sensor 254 in Figure 48 may be built into the tactile presentation device 20, or it may exist separately from the tactile presentation device 20. For example, the operation unit sensor 254 may be an information processing device carried by the user, such as a mobile terminal 60.

[0262] [If the control unit detected by the control unit sensor is not present in the control unit parameters] It is possible that the operating unit detected by the operating unit sensor 254 may not be present in the operating unit parameters. For example, In controllers used by users, such as game controllers, the user may want to change the control parts, such as knobs, and obtain a control feel that is suitable for the part being attached. • In the case of steering wheels for vehicles and other devices, there are times when the user wants to be able to replace them and obtain a steering feel that is suitable for the installed steering wheel.

[0263] If the operating unit detected by the operating unit sensor 254 is not present in the operating unit parameters, the mobile terminal 60 estimates the physical parameters. The user launches a predetermined application on the mobile terminal 60. The user uses a camera controlled by the application to photograph the operating unit 201 attached to the haptic presentation device 20. This allows the application to detect the size of the operating unit 201 from the image data. Therefore, the camera on the mobile terminal 60 is preferably a stereo camera or a LiDAR scanner. The application transmits the size of the operating unit 201 to the haptic presentation device 20. The communication unit 256 receives the size of the operating unit 201.

[0264] Furthermore, since the communication unit 256 receives the size but does not know the mass, a conversion formula is used to determine the mass of the operation unit 201 from its size. Alternatively, the application calculates the mass from the size using the conversion formula and transmits it to the haptic presentation device 20.

[0265] [Estimation of the operating part's mass through calibration] Next, the method by which the calibration unit 55 estimates the mass through calibration will be explained. When the operating unit 201 is attached, the calibration unit 55 operates the operating unit with an electric current pattern (rotates it in the case of a rotary type), and estimates the mass of the operating unit from the correspondence between the electric current and the position.

[0266] Figure 49 illustrates the method for estimating the mass of the control unit by calibration. First, Figure 49(a) illustrates the position of the rotary control unit 201. In the case of the rotary control unit 201, the position is simply the rotation angle of the rotation center. The rotation center is the center of the circle if the top surface of the control unit 201 is circular. When the calibration unit 55 rotates the rotary control unit 201, a larger current is required as the mass increases.

[0267] Figure 49(b) illustrates the relationship between the current required to change the position of the operating unit 201 and its position. The relationship between current and position shown in Figure 49(b) is an example for illustrative purposes. Generally, a larger current is required as the position changes. Also, the current has a constant relationship with the torque that rotates the operating unit, and the torque required to rotate the operating unit can be determined from the current. Furthermore, it is known that the current required to change the position is larger as the mass of the operating unit increases. The torque sensor 251 converts this current into torque.

[0268] If the relationship between the current I required to rotate the operating unit 201 to a certain position and its mass M, "I = αM", is known, then the mass M of the attached operating unit 201 can be estimated by measuring the current I required when the calibration unit 55 rotated the operating unit 201 to a certain position. α can be easily determined by measuring the current required to rotate several operating units 201 with known masses to a certain position.

[0269] In this way, the mass M of the operating unit 201 to which the calibration unit 55 is attached is estimated. For the size, a conversion formula for determining mass from size is used.

[0270] Therefore, if the operating unit detected by the operating unit sensor 254 is not among the operating unit parameters, the size and mass of the attached operating unit can be estimated not only by using the application on the mobile terminal 60, but also by calibration.

[0271] [Mass correction according to the installation location of the control unit] The degree of inclination of the control unit 201 differs depending on the installation location. For example, the inclination of the control unit 201 will differ when it is mounted on the steering wheel or on the center console. When the inclination differs, the feel of operating the press-type control unit will differ due to the effect of gravity. Therefore, the tactile presentation device 20 measures the inclination of the installation location of the control unit 201 using the acceleration sensor 28 and corrects the mass of the control unit 201.

[0272] Figure 50 is a diagram illustrating the correction of the mass of the operating unit 201. Figure 50(a) shows the operating reaction force F1 when the operating unit 201, which is installed in a location with zero inclination, is pressed. The operating reaction force F1 is, for example, the maximum value Tmax in Figure 11. Figure 50(b) shows the operating reaction force F2 when the operating unit 201, which is installed in a location with inclination θ, is pressed. Based on the relationship between the operating reaction forces F1, F2 and inclination θ shown in Figure 50(b), the operating reaction force F2 is as follows. F2 = F1 / cosθ Thus, a large operating reaction force is required when the installation site is sloped, but there is a correlation between the operating reaction force and mass. Therefore, the mass correction unit 261 corrects the mass of the operating unit 201 by treating the difference in operating reaction force as a difference in mass. The mass correction unit 261 corrects the mass of the operating unit 201 using a relationship such as "corrected mass = original mass / cosθ". In this way, even if the operating unit 201 is installed in a sloped location, a desirable operating feel can be controlled.

[0273] [Operation and Processing] Figure 51 is a flowchart illustrating the process of adjusting tactile presentation signals according to the physical parameters of the operating unit to which the tactile control system 110 is attached.

[0274] First, the tactile control system 110 determines the correspondence between physical parameters, including the mass and size of the operating part, and sensory parameters using methods such as the SD method (ST121).

[0275] Next, when the user attaches the control unit, the control unit sensor 254 detects the control unit attached by the user (ST122).

[0276] The tactile presentation device 20 determines whether or not there is a detected operating unit in the operating unit parameter 54 (ST123). The case where the operating unit sensor 254 cannot detect an ID is also included in the case where there is no detected operating unit in the operating unit parameter 54.

[0277] If the determination in step ST123 is Yes, the conversion model 15 converts the physical parameters registered in the operation unit parameters 54 into affective parameters (ST124). In this embodiment, the conversion model 15 calculates the affective parameters from the physical parameters as shown in Figure 22.

[0278] If the determination in step ST123 is No, the user takes a picture of the operating part with the application on the mobile terminal 60 and transmits its size and mass to the haptic presentation device (ST125).

[0279] The communication unit 256 receives the size and mass from the application of the mobile terminal 60 (ST126). Alternatively, as described above, the size and mass obtained by calibration by the calibration unit 55 may be used.

[0280] The conversion model 15 converts the estimated physical parameters (size, mass) into affective parameters (ST127).

[0281] The calculation unit 12 then generates a tactile feedback signal (ST128) using physical parameters such as size and mass (registered in the operation unit parameters 54 or estimated).

[0282] The arithmetic function unit 13 transmits a tactile presentation signal to the tactile presentation device 20. When the user rotates the operation unit 201, the processor 18 generates an operation signal. If the operation unit is a rotary type operation unit, the operation signal is, for example, the rotation angle. In the case of other operation units, the operation signal is the amount of operation of the operation unit. The tactile presentation unit 30 controls the actuator with the tactile presentation signal corresponding to the operation signal (ST129).

[0283] The calculation function unit 12 may also use the affective parameters converted from physical parameters in step ST127 to convert them back into physical parameters to generate a tactile presentation signal. A dedicated conversion model 15 may be provided for this second conversion.

[0284] Thus, the haptic control system 110 can estimate physical parameters even when an unregistered operating unit is attached. The calculation function unit 12, acting as an adjustment unit, generates haptic presentation signals based on the physical parameters, and can therefore adjust the haptic presentation signals according to the attached operating unit.

[0285] The adjustment unit is not limited to adjusting the "tactile presentation signal," but may also adjust the "operation signal," the "sensory presentation signal," the "sensory presentation" itself, or any combination thereof. Specifically, the following cases exist. • In this case, the processor 18 (an example of an operation detection unit) functions as an adjustment unit and reflects the adjustment in the "operation signal". • A case in which the calculation function unit 12 (an example of a signal generation unit) functions as an adjustment unit and reflects the adjustment in the "sensory presentation signal". • In this case, the tactile presentation unit 30 functions as an adjustment unit, and the adjustment is reflected in the "sensory presentation".

[0286] Furthermore, in this embodiment, since the conversion model estimates the sensory parameters from the physical parameters, a correlation between the sensory parameters and the physical parameters, which also reflects the physical parameters of the control unit, can be constructed. To add to this, this content can also be applied to content that is in line with "adjusting the sensory presentation signal." That is, if the physical parameters of the control unit change, such as when the control unit is replaced, and the actuator is driven in the same way as before the control unit 201 was replaced, the reproduced sensation, i.e., the sensory parameters, will be different. If the sensory parameters to be realized are constant, the physical parameters of the actuator can be adjusted by adjusting the sensory presentation signal, and sensory presentation can be made in line with the set sensory parameters.

[0287] Furthermore, Figure 52 is a flowchart illustrating a modified version of Figure 51, showing the process of adjusting the tactile presentation signal according to the physical parameters of the operating unit to which the tactile control system 110 is attached. The explanation of Figure 52 will mainly focus on the differences from Figure 51.

[0288] In Figure 52, if the determination in step ST123 (an example of a predetermined condition) is No, the calculation function unit 12 stops generating the sensory presentation signal (ST130).

[0289] This allows the sensory feedback signal to be stopped if a control unit with unknown physical parameters is attached, making it difficult to generate an appropriate sensory feedback signal.

[0290] Alternatively, the arithmetic function unit 12 may not stop generating sensory presentation signals, but may instead generate predetermined sensory presentation signals such as initial values.

[0291] [A haptic control system having a communication device (server) and a terminal device] Next, with reference to Figure 53, a haptic control system 111 having a communication device 70 (server) and a terminal device 80 will be described. Figure 53 shows the configuration of the haptic control system 111 as a second embodiment of the sensory control system 100 shown in Figure 45, along with the signal flow. In the description of Figure 53, the differences from Figure 45 will be explained in particular.

[0292] As shown in Figure 53, the tactile presentation device 20 of the terminal device 80 has a torque sensor 251, an operation unit sensor 254, and a communication unit 256. The communication device 70 has an operation unit parameter 54, a calibration unit 55, and a mass correction unit 261. The torque sensor 251, operation unit sensor 254, communication unit 256, operation unit parameter 54, calibration unit 55, and mass correction unit 261 can be the same as those described in Figure 45.

[0293] Figure 54 is a sequence diagram showing how the communication device 70 (server) and the terminal device 80 communicate to estimate the sensitivity parameters of the attached control unit.

[0294] In step ST131, the tactile control system 111 determines the correspondence between physical parameters, including the mass and size of the operating part, and sensory parameters using methods such as the SD method.

[0295] In step ST132, when the user attaches the control unit, the control unit sensor 254 detects the control unit attached by the user.

[0296] In step ST133, the terminal device 80 transmits the ID of the operating unit detected by the operating unit sensor 254 to the communication device 70. If the operating unit sensor 254 cannot detect the ID, the terminal device 80 transmits a message indicating that the ID was not detected to the communication device 70.

[0297] In step ST134, the communication device 70 determines whether or not there is an operating unit attached to the operating unit parameter 54 based on the operating unit ID received by the communication device 70.

[0298] If an operating unit is registered in the operating unit parameter 54, in step ST135, the conversion model 15 converts the physical parameters registered in the operating unit parameter 54 into affective parameters.

[0299] If the control unit is not registered in the control unit parameter 54, step ST136 sends a message to the terminal device 80 indicating that the communication device 70 is not registered.

[0300] In step ST137, the user takes a picture of the control panel using an application on the mobile terminal 60 and transmits its size and mass to the haptic presentation device 20.

[0301] In step ST138, the communication unit 256 receives the size and mass from the application of the mobile terminal 60.

[0302] In step ST139, the mobile terminal 60 transmits its size and mass to the communication device 70.

[0303] In step ST140, the conversion model 15 converts the estimated physical parameters (size, mass) into affective parameters.

[0304] In step ST141, the calculation function unit 12 generates a tactile presentation signal using physical parameters such as size and mass (registered in the operation unit parameters 54 or estimated).

[0305] In step ST142, the communication device 70 transmits a tactile feedback signal to the terminal device 80.

[0306] In step ST143, the tactile feedback unit 30 controls the actuator with a tactile feedback signal corresponding to the operation signal, in response to an operation signal from the user. At least one of the operation signal, the sensory feedback signal, and the sensory feedback may be controlled by either the communication device 70 or the terminal device 80.

[0307] [Main effects] According to the tactile control systems 110 and 111 of this embodiment, the physical parameters of the operating part are adjusted according to the size and mass of the operating part, so that even if the size and mass of the operating part change, the tactile sensation transmitted to the user operating it can be controlled to be a tactile sensation that is preferable to the user.

[0308] [others] For example, the operating unit in embodiment 3 is not limited to being detachable. For instance, in a system that implements multiple operating units, if multiple operating units with different knob sizes and designs are arranged, the system can recognize these differences and generate an appropriate tactile feedback.

[0309] Furthermore, the size and mass of the operating unit sensor 254 may be estimated by comparing it with a reference operating unit, rather than directly determining the size and mass of the operating unit through the application or calibration of the mobile terminal 60. For example, if an operating unit with an ID registered in the operating unit parameter 54 and an operating unit without an ID registered are placed in close proximity, both operating units will be captured in the image data. The processor 18 calculates the ratio of the size of the operating unit with an ID registered to the size of the operating unit without an ID registered, and estimates the size and mass of the operating unit without an ID registered by multiplying this ratio by the size and mass of the operating unit with an ID registered.

[0310] Note that the processor 18 is an example of an operation detection unit, the arithmetic function unit 12 is an example of a signal generation unit, and the tactile presentation unit 30 is an example of a sensory presentation unit.

[0311] [Additional notes for aspect 3] [Claim 1] Control panel and, An operation detection unit that detects the operation of the aforementioned operation unit and generates an operation signal, A signal generation unit that generates a sensory presentation signal based on the aforementioned operation signal, A sensory presentation unit that provides sensory information to the operator based on the aforementioned sensory presentation signal, A sensory control device comprising: an adjustment unit that adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation based on the physical characteristics of the operation unit. [Claim 2] The sensory control device according to claim 1, characterized in that the physical characteristics of the operating part include at least one physical parameter of the mass, diameter, radius, or overall length of at least a part of the operating part. [Claim 3] It has an operating unit sensor that detects the attached operating unit, The aforementioned operating unit sensor acquires identification information possessed by the operating unit to identify the physical characteristics of the operating unit, or, The sensory control device according to claim 1, characterized in that the physical characteristics of the operating unit are identified from image data captured by the operating unit. [Claim 4] The sensory control device according to claim 1, characterized in that the sensory presentation unit stops generating the sensory presentation signal when the physical characteristics of the operation unit satisfy predetermined conditions. [Claim 5] The sensory control device according to claim 1, characterized in that the operating unit is a press-type operating unit that accepts a press operation. [Claim 6] The sensory control device according to claim 1, characterized in that the operating unit is a slide operating unit that accepts slide operations. [Claim 7] The sensory control device according to claim 1, characterized in that the operating unit is a pivot operating unit that accepts tilting operations. [Claim 8] The sensory control device according to claim 1, characterized in that the operating unit is a rotary operating unit that accepts rotational operation. [Claim 9] The sensory control device according to claim 1, characterized in that the aforementioned sensory presentation signal is correlated with affective parameters. [Claim 10] The sensory control device according to claim 1, characterized in that the sensory presentation unit is a tactile presentation unit that provides tactile information to the operator. [Claim 11] The sensory control device according to claim 1, characterized in that at least a portion of the operating section is detachable. [Claim 12] A torque sensor that detects the torque required when the operating unit is driven by an actuator, A calibration unit that estimates the mass of the operating unit from the torque detected by the torque sensor based on a pre-defined relationship between torque and mass, A sensory control device according to claim 1, characterized by having the following: [Claim 13] An acceleration sensor that detects the tilt of the operating unit, A mass correction unit corrects the mass of the operating unit according to the tilt detected by the acceleration sensor, A sensory control device according to claim 1, characterized by having the following: [Claim 14] A sensory control method performed by a device having an operating unit, The steps include: detecting the operation of the control unit and generating an operation signal; The steps include generating a sensory presentation signal based on the aforementioned operation signal, The steps include providing sensory information to the operator based on the aforementioned sensory presentation signal, A step of adjusting at least one of the operation signal, the sensory presentation signal, and the sensory presentation based on the physical characteristics of the operation unit, A sensory control method characterized by having the following features. [Claim 15] A sensory control system comprising a communication device and a terminal device capable of communicating with each other, The aforementioned terminal device is Control panel and, An operation detection unit that detects the operation of the aforementioned operation unit and generates an operation signal, It has a sensory presentation unit that provides sensory presentations to the operator based on sensory presentation signals transmitted from the communication device, The aforementioned communication device is It has a signal generation unit that generates the sensory presentation signal based on the operation signal, The terminal device or communication device is a sensory control system comprising an adjustment unit that adjusts at least one of the operation signal, the sensory presentation signal, and the sensory presentation based on the physical characteristics of the operation unit. [Aspect 4] [Background technology] Conventionally, there are known devices that provide sensory feedback by stimulating a person. Here, sensory feedback includes tactile feedback, auditory feedback through sound, and visual feedback through image display, etc. Sensory feedback is adjusted by adjusting the signals that drive various devices.

[0312] Tactile systems that consider a fingertip model and provide click sensations are known (see, for example, Patent Document 4). Patent Document 4 discloses a technique for evaluating the response to shear vibrations generated by the fingertip during key presses by applying a mass-spring-damper system approximation of the fingertip to the parameter evaluation.

[0313] [Overview of the prefecture] [Problems the invention aims to solve] However, conventional technology does not account for deformation of elastic bodies such as fingers in the direction of operation, such as buckling in response to pressing operations, which limits the range of expressive capabilities of sensory presentation. In other words, fingers contain elastic bodies such as skin and flesh, but buckling phenomena caused by these elastic bodies are not reflected in sensory presentation.

[0314] In view of the above-mentioned problems, this embodiment aims to provide a technology that expands the range of expressive power of sensory presentation.

[0315] [Effects of the invention] This technology can provide a wider range of expressive capabilities in sensory presentation.

[0316] [Explanation of Embodiment 4] This embodiment describes a tactile control system 1 that outputs a sensory stimulus signal based on physical parameters including dynamic characteristics, and a sensory control method thereof. Dynamic characteristics are physical characteristics that include a time factor, for example, physical characteristics that change with time.

[0317] In this embodiment, the block diagram of Figure 1, the hardware configuration diagram of the haptic control system 1 in Figure 2, and other necessary explanations described in Embodiment 1 above will be used as references.

[0318] Conventionally, the load-displacement curves when a user presses on an operating device such as a switch are based on static characteristics that do not include a time factor, as they are based on the case of a rigid body being pressed. Therefore, information on the correspondence between sensory parameters and physical parameters has not been obtained in a state that reproduces the buckling phenomenon that actually occurs when a user presses with their finger.

[0319] In this embodiment, to approximate the situation when a user presses the control device with their finger, the control device is pressed using a finger model pressing device that has an elastic body (corresponding to the flesh and skin of the finger) integrated with a rigid body (corresponding to the bones of the finger) between the rigid body and the control device. By analyzing the change in the position of the control device [mm] and the two force sensor values ​​[N] between the elastic body and the control device when the finger model pressing device presses the control device, measurement and evaluation using the SD method was performed with a configuration that takes into account the fingers of a human body. The new physical parameters obtained as a result include dynamic characteristics, so correspondence information between the sensory parameters and physical parameters is generated in a state that reproduces the buckling phenomenon that occurs when a user actually presses with their finger.

[0320] Specifically, the following correlations are obtained. Note that the buckling period T1, fingertip impact period T3, and fingertip vibration period T4 are the periods shown in Figure 60(b) below, and details will be provided later. • Correlation between physical parameters (distance traveled by the operating tool during fingertip collision period T3, change in force sensor value during fingertip collision period T3, fingertip collision period T3) and sensory parameters (recovery sensation). • Correlation between physical parameters (position change during buckling period T1) and sensory parameters (feeling of being pulled in) • Correlation between physical parameters (fingertip vibration period T4) and sensory parameters (fatigue). [Example configuration of finger model pressure tool and operating tool] Figure 55 illustrates the static properties obtained by a rigid body press and the dynamic properties obtained by a finger model press 252 which is an integrated rigid body and elastic body. First, the load-displacement curve of the operating tool 250 using the rigid body press 253 can only represent static properties that do not include the time factor. The load-displacement curve 75 does not include the influence of the elastic body corresponding to the fleshy part of the finger 257, and therefore does not adequately represent the physical properties that contribute to the tactile sensation perceived by the operator.

[0321] Next, the pressing of the operating tool 250 by the finger model pressing tool 252 will be explained. First, the fleshy part 257 of the finger is an elastic body that deforms under stress. In addition, there is a bone 255 inside the finger that can be considered a rigid body. As will be described later, the finger model pressing tool 252 is designed to have the characteristics of both the fleshy part 257 and the bone 255. When the finger model pressing tool 252, which is an integrated rigid and elastic body, presses the operating tool 250, the operating reaction force and position change include dynamic characteristics with respect to time. In Figure 55, the dynamic characteristics 270 are shown as position change and two force sensor values ​​A and B. The two force sensor values ​​A and B detect the operating reaction force that the finger model pressing tool 252 generates on the operating tool 250, respectively. The two force sensor values ​​A and B are measured by different force sensors, which are located at the point where the fleshy part 257 of the finger contacts the operating tool 250 and at the rigid part inside the finger (corresponding to the bone 255), respectively. Further details are explained in Figure 59. As shown in the dynamic characteristics 270, the pressure applied to the operating device 250 by the finger model pressing device 252 can capture the movement of the finger over time, that is, the occurrence and change of sensation, thus obtaining a correlation close to the actual situation in which a user presses with their finger.

[0322] Figure 56 illustrates the relative positions of the finger and the operating tool 250 during finger deformation. The upper part of Figure 56 shows periods A to C, which can be read from the load-displacement curve 75. The lower part of Figure 56 schematically shows the deformation of the finger flesh corresponding to periods A to C.

[0323] As shown in the lower part of Figure 56, during period A, the position of the button portion 56 of the operating device 250 gradually lowers as the pressing force and rebound force of the finger are balanced.

[0324] During period B, deformation (buckling) occurs in the metal contact 57 of the operating tool 250, and its repulsive force disappears. The button portion 56 falls downward while maintaining its downward force. The operating reaction force is the difference compared to period A. Therefore, the operating reaction force at the contact point between the finger and the button is reduced.

[0325] During period C, the finger and the button portion 56 collide with the metal contact 57 again. At this time, the maximum operating reaction force is again generated at the contact point between the fingertip and the button portion 56. The collision also causes vibration of the button portion 56.

[0326] Figure 57 is a diagram illustrating the finger model pressing device 252. As explained in Figure 56, a finger is an elastic body whose fleshy portion 257 deforms. In addition, there is a bone 255 inside the finger that can be considered a rigid body. Therefore, the finger model pressing device 252, which has an elastic body 59 that contacts the button portion 56 and a rigid body 58 that presses the button portion 56 via the elastic body 59, serves as an appropriate model for when a finger presses the operating device 250.

[0327] [Generating a sensory input signal with a click-like feel] Figure 58 illustrates the generation of a tactile signal that provides a click sensation. A click sensation refers to the response of an input device, such as a button, or the tactile feedback of pressing a switch. In the case of a mechanical switch, the click sensation is obtained through the resistance and deformation of the metal contact 57, etc. However, how the click sensation is generated varies depending on the button structure.

[0328] Furthermore, in the operating device 250 in which sensory feedback signals are generated electrically, as in this embodiment, the click sensation is controlled by the current supplied to the actuator.

[0329] Figure 58(a) shows the actuator current value against time, and Figure 58(b) shows the operating reaction force against time. As the current value decreases rapidly in frame 283, the operating reaction force also decreases rapidly. The protrusion 284 in Figure 58(b) corresponds to the time when the current value decreases rapidly. As a result, when the user presses the operating tool 250 with their finger, they get a tactile sensation (click) similar to pressing a mechanical switch. The timing of the rapid decrease in current value and the amount of current decrease shown in Figure 58(a) are merely examples and can be adjusted as appropriate.

[0330] Figure 59(a) shows a functional configuration diagram of the press-type operating device, and Figure 59(b) shows a block diagram of the press-type operating device. The button portion 271 in Figure 59 is an example of the operating device 33 in Figure 2, and the VCM 263 is an example of the tactile presentation unit 30 in Figure 2. As shown in Figure 59(a), two force sensors A and B are arranged on the finger model pressing device 252. Force sensor A is positioned where the elastic body 59 of the finger model pressing device 252 and the button portion 271 come into contact, and force sensor B is positioned inside the rigid body 58 of the finger model pressing device 252. In this way, the buckling phenomenon can be monitored by the force sensor value A detected by force sensor A.

[0331] The block diagram in Figure 59(b) is just one example of a press-type operating device, but will be briefly explained. Note that the MCU circuit 262 is an example of the processor 18 in Figure 2, and the position sensor 264 is an example of the position sensor 27 in Figure 2. As shown in Figure 59(b), the MCU circuit 262 outputs a current to the VCM (Voice Coil Motor) 263 according to the amount of operation (position change) in which the button portion 271 of the operating device 250 is pressed. The VCM 263 applies an artificial reaction force to the button portion 271 that is proportional to the current. The finger model pressing device 252 presses the button portion 271 from the opposite side of the VCM 263, so the artificial reaction force is transmitted to the finger model pressing device 252. The artificial reaction force is measured by force sensors A and B.

[0332] [Dynamic characteristics obtained using a finger model pressure tool] Figure 60 illustrates the dynamic characteristics when the operating tool 250 is pressed by the finger model pressing tool 252. Figure 60(a) is a load-displacement curve 75 shown for reference, and Figure 60(b) is an example of the dynamic characteristics 270 when the operating tool 250 is pressed by the finger model pressing tool 252. In Figure 60(b), the horizontal axis represents time, and the vertical axis represents two force sensor values ​​A and B and position change 211. The unit of time is [msec], and the units of force sensor values ​​A and B are [N]. Note that the dynamic characteristics 270 vary greatly depending on the operating tool 250, and Figure 60(b) is only one example.

[0333] The dynamic characteristics (buckling period T1, fingertip drop period T2, fingertip impact period T3, fingertip vibration period T4) extracted from two force sensor values ​​A and B over time and the position change 211 over time will be explained with reference to Figures 60 and 61. Figure 61 is a diagram illustrating the temporal transition of the relative positions of the finger model pressing tool 252 and the operating tool 250.

[0334] The buckling period T1 is the period from the peak of the force sensor value B to the peak of the position change 211. Although it is difficult to see due to the scale, the force sensor value B is not constant and has a peak at the beginning of the buckling period T1. This peak will be explained in Figure 62. The peak of the force sensor value B corresponds to the maximum value of the operating reaction force in the load-displacement curve 75. Therefore, the buckling period T1 is the period from when the operating reaction force reaches its maximum value until the position change 211 reaches its maximum value. Figure 61(a) shows the relative positions of the finger model presser 252 and the button portion 56 at the beginning of the buckling period T1. At the beginning of the buckling period T1, the maximum value of the operating reaction force in the load-displacement curve 75 is obtained, so the elastic body 59 of the finger model presser 252 is greatly compressed. The arrow to the left of the button portion 56 indicates the direction of the position change.

[0335] The fingertip drop period T2 is the period from the peak of force sensor value B to the downward peak of force sensor value A. As shown in the load displacement curve 75, after the maximum value of the operating reaction force is obtained, the operating reaction force decreases sharply in order to produce a click sensation. As a result, the operating reaction force on the finger model presser 252 decreases, and the elastic body 59 of the finger model presser 252 begins to recover after the start of the fingertip drop period T2. This causes the force sensor value A to decrease during the fingertip drop period T2. Therefore, the fingertip drop period T2 is the period from when the maximum value of the operating reaction force is obtained until the elastic body of the finger model presser 252 recovers to its maximum. Figure 61(b) shows the relative position of the finger model presser 252 and the button portion 56 at the end of the fingertip drop period T2. Compared with Figure 61(a), it can be seen that the elastic body 59 of the finger model presser 252 has recovered.

[0336] The fingertip impact period T3 is the period from the downward peak of the force sensor value A to the upward peak of the force sensor value A. During the fingertip impact period T3, after the elastic body 59 of the finger model presser 252 has fully recovered as shown in Figure 61(b), the force sensor value A increases rapidly as the finger model presser 252 continues to be pressed. Therefore, the fingertip impact period T3 is the period from when the elastic body 59 of the finger model presser 252 has fully recovered until the elastic body 59 is most deeply compressed. Figure 61(c) shows the relative positions of the finger model presser 252 and the button portion 56 at the end of the fingertip impact period T3. Compared with Figure 61(b), it can be seen that the elastic body 59 of the finger model presser 252 is deeply compressed.

[0337] The fingertip vibration period T4 is the period from the upward peak of the force sensor value A until the fluctuation of the force sensor value A settles within a constant value. Since the operating reaction force has already been reduced to produce a click sensation, even if the position change 211 continues to increase due to pressing, the force sensor A decreases rapidly. After that, the position change 211 stops increasing (the finger model presser 252 also stops moving), so the force sensor value B also becomes less likely to change, and the force sensor value A vibrates like chattering. Therefore, the fingertip vibration period T4 is the period until the most pressed elastic body recovers and stabilizes. Figure 61(d) shows the relative position of the finger and the button part 56 at the end of the fingertip vibration period T4. Compared with Figure 61(c), it can be seen that the elastic body 59 of the finger model presser 252 has recovered.

[0338] The buckling period T1, fingertip drop period T2, fingertip impact period T3, and fingertip vibration period T4 described above are examples of dynamic characteristics. Furthermore, changes in force sensor values ​​A and B, and position changes 211 can be extracted during each of the buckling period T1, fingertip drop period T2, fingertip impact period T3, and fingertip vibration period T4. In this embodiment, these can also be used as dynamic characteristics.

[0339] Thus, the dynamic characteristics may be physical characteristics that include the time change of at least one of the operating reaction force and the operating amount associated with the operation of a predetermined operating tool 250. These physical characteristics are those that realize tactile feedback when the elastic body 59 of the finger model pressing tool 252 is brought into contact with the operating tool 250 for operation.

[0340] Figure 62 is a diagram that explains the dynamic characteristics in more detail, along with the periods A to C described above. The upper left portion of Figure 62 is an overall diagram including the start and end of the dynamic characteristics, and the lower right portion of Figure 62 is an enlarged view of the dynamic characteristics within the frame 212 of the upper left portion of Figure 62. The lower right portion of Figure 62 shows the correspondence between the dynamic characteristics and periods A to C. The force sensor value A detected by force sensor A changes significantly due to the compression and restoration of the elastic body 59. The force sensor value B detected by force sensor B is less affected by the deformation of the elastic body 59, so the change is small.

[0341] In the lower right portion of Figure 62, the buckling period T1, fingertip drop period T2, fingertip impact period T3, and fingertip vibration period T4 are also shown, as explained in Figure 60. The peak of force sensor B (the starting point of buckling period T1 and fingertip drop period T2), which was not clear in Figure 60, is now clearly visible.

[0342] [Dynamic characteristics that correlate with emotional parameters] Among the dynamic characteristics described in Figures 60 and 62, some correlate with the affective parameters. The appropriate dynamic characteristics that correlate with the affective parameters are the physical parameters in this embodiment.

[0343] The tactile control system 1 is evaluated using the SD method to assess appropriate dynamic characteristics that correlate with affective parameters. For this purpose, multiple control tools 250 with different dynamic characteristics are provided.

[0344] Figure 63 shows the dynamic characteristics of multiple operating tools 250 with different dynamic characteristics when pressed by a finger model pressing tool 252. In this embodiment, 25 operating tools 250 were prepared for explanatory purposes, and the dynamic characteristics of each of the 25 operating tools 250 were measured. Figure 63 shows the dynamic characteristics of four of these operating tools 250. In each of Figures 63(a) to (d), the upper figure shows the dynamic characteristics 270 for the entire period (approximately 1 second) during pressing, and the lower figure shows an enlarged view of the dynamic characteristics 270 before and after the buckling period T1, fingertip drop period T2, fingertip impact period T3, and fingertip vibration period T4.

[0345] <Determination of physical parameters that correlate with emotional parameters> Figure 64 is a flowchart illustrating the process of determining physical parameters that correlate with affective parameters.

[0346] In step ST151, the tactile control system 1 measures the dynamic characteristics when each of the 25 operating tools 250 is pressed by the finger model pressing tool 252.

[0347] Next, in step ST152, the input unit 4 receives the expression degree for each affective parameter using the SD method for the 25 control tools 250.

[0348] Next, in step ST153, the processor 101 obtains a set of dynamic characteristics and expressiveness values ​​for each control device 250 for each affective parameter.

[0349] Next, in step ST154, the processor 101 calculates the correlation coefficient between the dynamic characteristics and the expressiveness for each affective parameter.

[0350] Next, in step ST155, the processor 101 determines the dynamic characteristics for which the absolute value of the correlation coefficient is large. A large absolute value of the correlation coefficient means, for example, 0.5 or greater.

[0351] Next, in step ST156, the processor 101 applies the multiple regression analysis described in equation 5 to the physical parameters and emotional parameters that have a high correlation with the emotional parameters to create a transformation model 15.

[0352] Figure 65 is a scatter plot of the dynamic characteristics and expression frequencies of each control tool 250 for a certain affective parameter acquired by the processor 101 in step ST153. In Figure 65, the horizontal axis shows the affective parameter "recovery present (or absent)," and the vertical axis shows the buckling period T1. There is generally an upward trend between the buckling period T1 and the expression frequency of "recovery present (or absent)." The correlation coefficient is 0.82.

[0353] Figure 66 is a scatter plot of the dynamic characteristics and expression frequencies of each operating tool 250 for a certain affective parameter acquired by the processor 101 in step ST153. In Figure 66, the horizontal axis shows the affective parameter "feeling of being sucked in (or not)," and the vertical axis shows the change in position during the fingertip collision period T3. There is a general downward trend between the change in position during the fingertip collision period T3 and the expression frequency of "feeling of being sucked in (or not)." The correlation coefficient is 0.65.

[0354] Figure 67 is a scatter plot of pairs of dynamic characteristics and expression frequencies for each operating tool 250 for a certain affective parameter acquired by the processor 101 in step ST153. In Figure 67, the horizontal axis shows the affective parameter "feeling of recovery present (or absent)," and the vertical axis shows the change in operating reaction force (force sensor value A) during the fingertip vibration period T4. There is generally an upward trend in the relationship between the change in operating reaction force during the fingertip vibration period T4 and the expression frequency of "feeling of recovery present (or absent)." The correlation coefficient is 0.78.

[0355] The processor 101 relates the affective parameters and dynamic characteristics shown in Figures 65, 66, and 67 using the least squares method (an example of regression analysis). The strength of the correlation between the affective parameters and dynamic characteristics is estimated by the correlation coefficient using the least squares method.

[0356] Figure 68 shows a list of correlation coefficients between each affective parameter and each dynamic characteristic. In Figure 68, the row headings represent affective parameters, and the column headings represent the dynamic characteristics of the control device 250. In Figure 68, correlation coefficients of 0.5 or higher are highlighted with diagonal lines. Therefore, it can be seen that dynamic characteristics with large correlation coefficients are appropriate for physical parameters.

[0357] In this way, when each operating tool 250 is pressed by the finger model pressing tool 252, physical parameters with a high correlation to the emotional parameters are determined, and the processor 101 can create a transformation model 15 by applying the multiple regression analysis described in Equation 5 to the physical parameters with a high correlation to the emotional parameters and to the emotional parameters. The physical parameters P1 to Pn used in Equation 5 are those with a large correlation coefficient determined in step ST154. The multiple regression analysis is explained in Equation 5, Figures 22 and 23 of Embodiment 1. Therefore, the coefficient of determination B for each operating tool 250 11 ~B mn This allows us to determine the value, and a conversion model 15 like the one shown in Figure 23 is obtained for each operating tool 250.

[0358] [A haptic control system having a communication device (server) and a terminal device] Next, with reference to Figure 69, a haptic control system 2 having a communication device 70 (server) and a terminal device 80 will be described. The block diagram of the haptic control system 2 is the same as that in Figure 20.

[0359] Figure 69 is a sequence diagram showing how the communication device 70 (server) and the terminal device 80 communicate to estimate the sensory parameters of the attached operating device 250.

[0360] In step ST161, the communication device 70 and the terminal device 80 communicate, and the dynamic characteristics of each of the 25 operating tools 250 are measured by pressing them with the finger model pressing tool 252.

[0361] Next, in step ST162, the input unit 4 receives the expression degree for each affective parameter using the SD method for the 25 control tools 250.

[0362] Next, in step ST163, the terminal device 80 transmits the expression frequency to the communication device 70.

[0363] Next, in step ST164, the processor 14 obtains a set of dynamic characteristics and expressiveness values ​​for each control device 250 for each affective parameter.

[0364] Next, in step ST165, the processor 14 calculates the correlation coefficient between the dynamic characteristics and the expressiveness for each affective parameter.

[0365] Next, in step ST166, the processor 14 determines the dynamic characteristics for which the absolute value of the correlation coefficient is large. A large absolute value of the correlation coefficient means, for example, 0.5 or greater.

[0366] Next, in step ST167, the processor 14 applies the multiple regression analysis described in equation 5 to the physical parameters and emotional parameters that have a high correlation with the emotional parameters to create a transformation model 15.

[0367] [Main effects] As described above, the tactile control system 1 of this embodiment can extract dynamic characteristics correlated with sensory parameters by pressing the operating tool 250 with the finger model pressing tool 252. Therefore, a conversion model can be created that converts sensory parameters into these dynamic characteristics, and thus a sensory presentation signal with desirable dynamic characteristics can be generated.

[0368] [others] For example, while Embodiment 2 describes a press-type operating device, the same can be applied to a rotary-type operating device that accepts rotational operation. In the case of a rotary-type operating device, the rotation angle is a change in position, and the resistance force to rotation is the operating reaction force.

[0369] Furthermore, although a finger model presser 252 having only one type of elastic body 59 has been described, the finger model presser 252 may have multiple types of elastic bodies with different elastic forces on the side that contacts the button portion 56. These multiple types of elastic bodies with different elastic forces may include, for example, an elastic body corresponding to skin, an elastic body corresponding to flesh, etc. Also, these multiple types of elastic bodies with different elastic forces may be arranged in layers such that the elastic force increases as they get closer to the rigid body 58. This allows for the construction of a finger model presser 252 that exhibits dynamic characteristics closer to human touch.

[0370] Furthermore, the shape of the finger model pressure tool 252 may be a simple cube or it may mimic the shape of a finger. The finger shapes may differ in size and shape, representing the fingers of men, women, adults, children, and different races.

[0371] [Additional notes for aspect 4] [Claim 1] A reception step that accepts input of a sensory parameter indicating the degree of sensory expression when operating a control tool, A conversion step that converts the received sensory parameters into physical parameters that correlate with the sensory parameters from among multiple types of physical parameters included in the physical characteristics related to sensory stimuli, Includes an output step that outputs a sensory stimulus signal based on the converted physical parameters, The aforementioned physical characteristics include dynamic characteristics, as well as sensory control methods. [Claim 2] The sensory control method according to claim 1, wherein the dynamic characteristics are physical characteristics that include the time change of at least one of the operating reaction force and the operating amount associated with the operation of a predetermined operating tool. [Claim 3] The sensory control method according to claim 2, wherein the physical properties are physical properties that realize sensory presentation when operating a finger model pressing tool, which includes a rigid body and an elastic body, by bringing the elastic body into contact with the predetermined operating tool. [Claim 4] The sensory control method according to claim 1, wherein the physical parameter is the buckling period. [Claim 5] The sensory control method according to claim 1, wherein the physical parameter is the fingertip drop period. [Claim 6] The sensory control method according to claim 1, wherein the physical parameter is the fingertip collision period. [Claim 7] The sensory control method according to claim 1, wherein the physical parameter is the fingertip vibration period. [Claim 8] The sensory control method according to claim 1, wherein the physical parameters are correlated with the sensory parameters. [Claim 9] The sensory control method according to claim 1, characterized in that the operating device is a press-type operating device that accepts a pressing operation. [Claim 10] The sensory control method according to claim 1, characterized in that the operating device is a rotary operating device that accepts rotational operation. [Claim 11] An input unit that accepts input of a sensory parameter indicating the degree of sensory expression when operating a control device, A conversion model that converts the affective parameters received by the input unit into physical parameters that correlate with the affective parameters from among multiple types of physical parameters included in the physical characteristics related to sensory stimuli, The sensory presentation unit includes a sensory presentation unit that outputs a sensory stimulus signal based on the physical parameters converted by the conversion model, The aforementioned physical characteristics include dynamic characteristics of the device. [Claim 12] A sensory control system comprising a communication device and a terminal device capable of communicating with each other, The terminal device has an input unit that receives input of a sensory parameter indicating the degree of sensory expression when operating a control tool. The communication device has a conversion model that converts the affective parameters transmitted from the terminal device into physical parameters that correlate with the affective parameters from among a plurality of types of physical parameters included in the physical characteristics related to sensory stimuli, The terminal device has a sensory presentation unit that outputs a sensory stimulus signal based on the physical parameters converted by the conversion model, The aforementioned physical characteristics include dynamic characteristics, making it a sensory control system. [Claim 13] The device, An input unit that accepts input of a sensory parameter indicating the degree of sensory expression when operating a control device, A conversion model that converts the affective parameters received by the input unit into physical parameters that correlate with the affective parameters from among multiple types of physical parameters included in the physical characteristics related to sensory stimuli, The aforementioned conversion model functions as a sensory presentation unit that outputs sensory stimulus signals based on the converted physical parameters, The aforementioned physical characteristics include a program that also includes dynamic characteristics.

[0372] [others] Although the best mode for carrying out the present invention has been described above using various embodiments, the present invention is not limited in any way to these embodiments, and various modifications and substitutions can be made without departing from the spirit of the invention. For example, the functions included in each component, each step, etc., can be rearranged in a way that is not logically contradictory, and multiple components or steps, etc., can be combined into one or divided.

[0373] This application claims priority based on Japanese Patent Application No. 2021-084696 filed with the Japan Patent Office on May 19, 2021, Japanese Patent Application No. 2022-079095 filed with the Japan Patent Office on May 12, 2022, Japanese Patent Application No. 2022-079099 filed with the Japan Patent Office on May 12, 2022, and Japanese Patent Application No. 2022-079128 filed with the Japan Patent Office on May 13, 2022, and the entire contents of Japanese Patent Application Nos. 2021-084696, 2022-079095, 2022-079099, and 2022-079128 are incorporated into this application. [Explanation of Symbols]

[0374] 1, 2 Tactile control systems 3 Input / Output Devices 4 Input section 5 Display section 6, 10 Main control unit 7, 14, 18, 41, 101 processors 8, 11 Storage section 9 Network 12, 13 Arithmetic Function Unit 15. Sensory Parameter-Physical Parameter Conversion Model 16. Sensory Database 20, 40 Tactile presentation devices 21 Moving parts 24 bobbins 25 coils 26 Spring component 27 Position Sensor 28 Accelerometer 29 Variable operating range section 30, 43 Tactile presentation section 31 York 31a Outer yoke 31b Center York 32 magnets 33, 42 Operating device 39 Actuators 43a Resistance Torque Generator 43b Rotational Torque Generator 45 sensors 70 Communication equipment 80 Terminal devices 100 Sensory Control Systems 102 Sensory presentation section

Claims

1. A reception step that accepts sensitivity parameters indicating the degree of sensory expression in response to sensory presentation, A conversion step of converting the received sensory parameters into physical parameters that correlate with the sensory parameters from among multiple types of physical parameters included in the physical characteristics related to sensory presentation, An output step that outputs a sensory feedback signal based on the converted physical parameters, Includes, A sensory control method in which, when a sensory parameter is input to a terminal device, information on physical parameters correlated with the sensory parameter is received from a communication device via a network, and tactile sensations are presented using tactile presentation signals based on those physical parameters.

2. The terminal device, after receiving the input of the emotional parameters, transmits the information of the received emotional parameters to the communication device via the network. The communication device converts the emotional parameters into physical parameters that correlate with them. The terminal device generates tactile feedback signals based on physical parameters. The sensory control method according to claim 1.

3. The communication device extracts and communicates physical parameters that correlate with the emotional parameters. The sensory control method according to claim 1.

4. The aforementioned communication device is connected to each of the multiple terminal devices via a network. The sensory control method according to claim 1.

5. Multiple conversion models are stored in the communication device, depending on the application, and different conversion models are used depending on the application required by the terminal device. The sensory control method according to claim 1.

6. The aforementioned communication device can communicate with multiple terminal devices via a network and performs the transmission, reception, and distribution of haptic feedback signals in connection with live content distribution, content data updates, or user interaction or game competition. The sensory control method according to claim 1.

7. A common set of emotional parameters is assigned to each terminal device. The sensory control method according to claim 6.

8. Individual sensitivity parameters are set for each terminal device. The sensory control method according to claim 6.

9. While some emotional parameters are set to be common across each terminal device, other emotional parameters are set individually. The sensory control method according to claim 6.

10. When multiple terminal devices are used to allow users to work in a common VR or AR environment, the sensitivity parameter indicating the magnitude of the sensation is common to all terminal devices, while the sensitivity parameter indicating the sharpness of the sensation is adjusted according to the user's preference for each terminal device. The sensory control method according to claim 6.

11. If the aforementioned communication device is installed in a vehicle, Based on communication between vehicles via a network, communication with road installations such as traffic signs, or distribution of traffic information from a server, the communication device receives tactile signals for warnings, etc. The sensory control method according to claim 1.

12. The aforementioned communication device receives tactile information related to telemedicine via a network. The sensory control method according to claim 1.

13. The aforementioned communication device receives tactile information associated with the remote operation of an industrial robot via a network. The sensory control method according to claim 1.

14. The aforementioned tactile sensation is customized based on sensory values. The sensory control method according to claim 12 or claim 13.

15. The aforementioned communication device receives tactile information regarding the feel of the product, how it fits, or the writing experience through a writing instrument, via the network. The sensory control method according to claim 1.

16. The aforementioned tactile sensation or wearing sensation is customized based on sensory values. The sensory control method according to claim 15.

17. The aforementioned communication device receives tactile information via a network, such as the sensation of users in remote locations shaking hands, touching each other, or interacting with animals like pets. The sensory control method according to claim 1.

18. The terminal device uses or combines thermal sensation presentation as a tactile presentation unit. The sensory control method according to claim 1.

19. A reception means for receiving sensitivity parameters that indicate the degree of sensory expression in response to sensory presentation, A conversion means that converts the received sensory parameters into physical parameters that correlate with the sensory parameters from among a plurality of types of physical parameters included in the physical characteristics related to sensory presentation, An output means that outputs a sensory presentation signal based on converted physical parameters, Includes, A sensory control device that, upon input of a sensory parameter into a terminal device, receives information on physical parameters correlated with that sensory parameter from a communication device via a network, and presents tactile sensations using tactile presentation signals based on those physical parameters.

20. A sensory control system having a communication device and a terminal device, The aforementioned terminal device is A reception means for receiving sensitivity parameters that indicate the degree of sensory expression in response to sensory presentation, A conversion means that converts the received sensory parameters into physical parameters that correlate with the sensory parameters from among a plurality of types of physical parameters included in the physical characteristics related to sensory presentation, An output means that outputs a sensory presentation signal based on converted physical parameters, Includes, A sensory control system that, upon input of a sensory parameter to the terminal device, receives information of a physical parameter correlated with the sensory parameter from the communication device via a network, and presents tactile sensations using tactile presentation signals based on the physical parameter.

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