Information processing device, information processing method, and program

Abstract

The present technology relates to an information processing device, an information processing method, and a program that make it possible to improve entertainment properties. An operation body, which performs a motion that is in accordance with predetermined motion data, is controlled so as to perform the motion in conjunction with the external state and / or the internal state of the operation body, the motion that is in accordance with predetermined motion data being emphasized or suppressed. The present technology can be applied to, for example, an operation body that performs motions of an actually existing robot or a virtual character.

Description

Information processing device, information processing method, and program

[0001] The present technology relates to an information processing device, an information processing method, and a program, and in particular to an information processing device, an information processing method, and a program that can improve entertainment value, for example.

[0002] For example, Patent Document 1 describes a technique for emphasizing the motion of animation.

[0003] Japanese Patent Application Laid-Open No. 2003-132363

[0004] If the motions of the moving body performing the animation or other motions are uniformly emphasized, the moving body will lack entertainment value.

[0005] The present technology has been made in view of such circumstances, and is intended to make it possible to improve the entertainment value of moving objects.

[0006] The information processing device or program of the present technology is an information processing device that has a control unit that controls a moving body to perform a motion that emphasizes or suppresses the motion in accordance with specified motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion in accordance with the specified motion data, or a program for causing a computer to function as such an information processing device.

[0007] The information processing method of the present technology is an information processing method that includes controlling a moving body to perform a motion that emphasizes or suppresses the motion in accordance with predetermined motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion in accordance with the predetermined motion data.

[0008] In this technology, the moving body is controlled to perform a motion that emphasizes or suppresses the motion according to predetermined motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion according to the predetermined motion data.

[0009] The information processing device may be an independent device or an internal block constituting a single device.

[0010] The program can be provided by transmitting it via a transmission medium or by recording it on a recording medium.

[0011] 1 is a perspective view showing an example of the external configuration of an embodiment of a pet-type robot as a moving body to which the present technology is applied. FIG. 2 is a block diagram showing an example of the electrical configuration of the moving body 10. FIG. 3 is a diagram showing an example of display of an eye image by a display unit 43. FIG. 4 is a diagram explaining an overview of a motion emphasizer. FIG. 5 is a diagram explaining a cartoon animation filter. FIG. 6 is a diagram explaining generation of modified data (emphasis motion data) for performing an emphasis motion that emphasizes a default motion in a motion emphasizer. FIG. 7 is a diagram explaining an emphasis coefficient E. FIG. 8 is a diagram explaining a first example of a limit coefficient. FIG. 9 is a diagram explaining a second example of a limit coefficient. FIG. 10 is a diagram explaining an example of setting the emphasis coefficient E for each joint. FIG. 11 is a diagram explaining an addition coefficient a(t). FIG. 12 is a diagram explaining inconveniences of modified data that arise for repeat portions. FIG. 13 is a diagram explaining generation of repeat portions of modified data. FIG. 14 is a diagram explaining generation of modified data (suppression motion data) for performing a suppression motion that suppresses a default motion in a motion emphasizer. FIG. 15 is a diagram explaining generation of modified data (emphasis motion data) for performing an emphasis motion that emphasizes a default motion by adding speed and slowness to the default motion in a motion emphasizer. 1 is a diagram illustrating an example of a default motion and an emphasis motion (modified motion) that emphasizes the default motion. FIG. 2 is a diagram illustrating an example of a default motion and an emphasis motion (modified motion) that suppresses the default motion. FIG. 3 is a flowchart illustrating an example of the processing of a moving body 10. FIG. 4 is a flowchart illustrating an example of the processing of a moving body 10 that performs a dance motion in time with clapping or music. FIG. 4 is a diagram illustrating an example of a motion performed by the moving body 10. FIG. 5 is a diagram illustrating an example of a motion performed by the moving body 10. FIG. 6 is a diagram illustrating an example of an external situation and an internal state, and a motion performed in conjunction with the external situation or the internal state. FIG. 7 is a diagram illustrating an example of an external situation and a mode of emphasizing or suppressing a motion performed in conjunction with the external situation. FIG. 8 is a diagram illustrating an example of an internal state and a mode of emphasizing or suppressing a motion performed in conjunction with the internal state. FIG. 9 is a diagram illustrating an example of a personality as an internal state, and adjustment of motion elements in emphasizing or suppressing a motion performed in conjunction with the personality.Fig. 1 is a diagram showing an example of the configuration of an embodiment of an information processing system that provides a virtual character as a moving body to which the present technology is applied. Fig. 2 is a perspective view showing an example of the external configuration of an embodiment of a toy robot that is a moving body to which the present technology is applied. Fig. 3 is a diagram explaining an example of modified motion (emphasized motion) that emphasizes the default motion of moving a moving body 210 by rollers 212. Fig. 4 is a block diagram showing an example of the configuration of an embodiment of a computer to which the present technology is applied.

[0012] <Pet-type robot applying this technology>

[0013] FIG. 1 is a perspective view showing an example of the external configuration of an embodiment of a pet-type robot as a moving body to which the present technology is applied.

[0014] In FIG. 1, a moving body 10 is a robot that exists in reality (in the real world) and autonomously performs various motions.

[0015] In Fig. 1, the moving body 10 is a dog-shaped pet robot having a head, a body, four legs, and a tail. Each part of the moving body 10 is provided with an actuator (not shown). The actuators drive the joints and the like, allowing the moving body 10 to perform natural motions similar to those of an actual dog. For example, the moving body 10 can perform various motions such as walking, nodding, tilting its head, swinging its hips, erecting its ears, wagging its tail, and barking.

[0016] As long as the moving body 10 can perform a motion, there is no particular limitation on its shape. In Fig. 1, a dog pet robot is used as the moving body 10, but the moving body 10 may be a robot in the shape of any animal other than a dog, such as a cat or a human, or a robot in the shape of any other than an animal.

[0017] The moving body 10 senses various physical quantities and, based on sensor information obtained as a result of the sensing, recognizes the external situation of the moving body 10, such as user actions on the moving body 10. The moving body 10 also stores internal state information representing the internal state of the moving body 10, such as the emotions, personality, and instincts (desires), in an internal memory (not shown), and updates the internal state information stored in the internal memory as appropriate based on the external situation, etc. The moving body 10 then autonomously performs various motions based on the external situation and / or the internal state, etc., represented by the internal state information.

[0018] As described above, the moving body 10 autonomously performs a motion based on the external situation and / or its internal state, etc., and therefore does not necessarily perform a motion in accordance with the user's instructions. That is, the moving body 10 may perform a motion in accordance with the user's instructions, or may not perform a motion in accordance with the user's instructions but may perform a motion that expresses its internal state, such as its emotions or instincts (desires), at that time.

[0019] Specifically, for example, when the internal state indicates that the battery is low, the moving body 10 moves to a charging station (not shown) and performs a motion to charge. Also, for example, when the internal state indicates a desire (instinct) to be loved by a user and the external situation indicates that the user is nearby, the moving body 10 performs various motions to attract the user's interest. After performing various motions, the moving body 10 learns which motions the user finds pleasing and can increase the frequency with which it performs such motions that the user finds pleasing.

[0020] FIG. 2 is a block diagram showing an example of the electrical configuration of the operating body 10. As shown in FIG.

[0021] In FIG. 2, the moving body 10 includes a sensor device 21, an information processing device 22, and a motion executing device 23.

[0022] The sensor device 21 includes various sensors, such as a camera, a microphone, an illuminance sensor, a ToF (Time of Flight) sensor, a human sensor, a touch sensor, an inertial sensor, and a temperature sensor.

[0023] The camera captures images of the surroundings, and the operating body 10 can perform SLAM (Simultaneous Localization and Mapping) using the images captured by the camera.

[0024] The microphone collects (collects) surrounding sounds. The sounds collected by the microphone include the user's speech and surrounding environmental sounds. The moving body 10 can perform voice recognition of the user's speech collected by the microphone, identify environmental sounds, and localize sound sources (estimate the position of sound sources).

[0025] The illuminance sensor detects the ambient illuminance (brightness). The ToF sensor detects the distance to surrounding objects. The human presence sensor detects people, including the user, in the vicinity. The touch sensor detects contact by the user, etc. For example, the touch sensor detects contact such as touching, stroking, tapping, or pushing on parts of the moving body 10, such as the top of the head, under the chin, or back. The inertial sensor detects the (angular) velocity, (angular) acceleration, and rotation angle of parts of the moving body 10, such as the head or torso. The temperature sensor detects the temperature of the moving body 10.

[0026] Each sensor of the sensor device 21 senses various physical quantities and supplies sensor information such as images, sounds, and illuminance obtained by the sensing to the information processing device 22.

[0027] The information processing device 22 performs various information processes including control of the operating body 10 based on the sensor information etc. from the sensor device 21. The information processing device 22 has a trigger detection section 31 and a control section 32.

[0028] The trigger detection unit 31 is supplied with sensor information from the sensor device 21 and internal state information from the control unit 32. The trigger detection unit 31 detects motion events, which are events that trigger various motions, based on the sensor information and / or internal state information, etc. When the trigger detection unit 31 detects a motion event, it supplies motion information indicating the motion corresponding to the motion event to the control unit 32.

[0029] Here, a motion to be performed for a motion event can be associated with the motion event in advance, and the motion associated with the motion event can be adopted as the motion corresponding to the motion event. Also, a learning model that has learned the relationship between an event and the motion that can be performed for that event can be prepared, and the motion that the learning model outputs in response to the input of a motion event can be adopted as the motion corresponding to the motion event.

[0030] The control unit 32 stores internal state information and motion data in its internal memory. The internal state information is information representing various internal states of the moving body 10, such as the emotions, personality, instincts, battery status, and operating / failure status of each part of the moving body 10. The internal state information is updated as appropriate based on sensor information, the battery status of the moving body 10, and the operating / failure status of each part of the moving body 10. The motion data is data for causing the moving body 10 to perform various motions and is designed by the creator for each motion. The motion data for a predetermined motion is, for example, time-series data such as the joint angles of each joint of the moving body 10, sounds to be output from the sound output unit 42, and images to be displayed on the display unit 43 as eyes when the moving body 10 is made to perform the predetermined motion. Motion data designed by the creator and preset in the moving body 10 is also referred to as default data (predetermined motion data). A motion based on the default data is also referred to as default motion.

[0031] The control unit 32 controls the moving object 10 to perform the motion represented by the motion information from the trigger detection unit 31. That is, the control unit 32 controls the drive unit 41, sound output unit 42, and display unit 43 of the motion execution device 23 in accordance with motion data that causes the moving object 10 to perform the motion represented by the motion information. In this way, the control unit 32 causes the moving object 10 to perform the motion in accordance with the motion data.

[0032] The motion of the moving body 10 controlled by the control unit 32 includes moving each part of the moving body 10, such as the legs, head, mouth, ears, and tail, which physically move, as well as outputting sounds and displaying eyes. Examples of sound output include outputting cries, outputting chewing sounds when (virtually) eating food, outputting sound effects using onomatopoeia to express footsteps when walking, and outputting moving motions. Regarding eye display, the eyes of the moving body 10 are expressed by displaying images of eyes on the display unit 43, and eye display refers to displaying images of eyes on the display unit 43. In addition to moving each part of the moving body 10, the moving body 10 can output sounds such as cries and display images of eyes as motions, allowing for a wide range of expression.

[0033] The control unit 32 is supplied with motion information from the trigger detection unit 31 and sensor information from the sensor device 21. The control unit 32 controls the moving object 10 to perform a motion that emphasizes or suppresses a default motion in conjunction with the external situation of the moving object 10 recognized based on the sensor information and / or the internal state of the moving object 10 represented by the internal state information. For example, the control unit 32 controls the moving object 10 in accordance with modified data, which is motion data generated using default data and causes the moving object 10 to perform a motion that emphasizes or suppresses the default motion.

[0034] The modified data can be generated in advance (offline) using default data in a server (not shown), for example, and provided to the operating body 10 as a data update. In this case, the operating body 10 can download the modified data from the server and store it in the control unit 32. The modified data can also be generated in real time in the control unit 32 using the default data.

[0035] As described above, the control unit 32 controls the moving body 10 to perform a motion that emphasizes or suppresses the default motion in conjunction with the external situation of the moving body 10 and / or the internal state of the moving body 10. As a result, the moving body 10 does not uniformly perform a motion that emphasizes or suppresses the default motion, but performs a motion that emphasizes or suppresses the default motion in conjunction with the surrounding situation and the internal state. For example, the moving body 10 performs a motion that emphasizes or suppresses the default motion in conjunction with the surrounding situation, such as whether or not a user as a master is nearby, and the internal state, such as the emotional state. This can improve the entertainment value of the moving body 10.

[0036] The motion executing device 23 performs processing for the moving body 10 to perform a motion (processing that becomes the motion of the moving body 10) under the control of the control unit 32. The motion executing device 23 has a drive unit 41, a sound output unit 42, and a display unit 43.

[0037] The drive unit 41 is an actuator that moves each part of the physically moving moving body 10, such as the legs, head, mouth, ears, and tail, and moves each part according to the control of the control unit 32. The sound output unit 42 outputs various sounds such as cries, chewing sounds, and sound effects according to the control of the control unit 32. The display unit 43 displays an image of the eye in a state according to the control of the control unit 32.

[0038] FIG. 3 is a diagram showing an example of an eye image displayed by the display unit 43. As shown in FIG.

[0039] The operating body 10 has displays corresponding to the left and right eyes, respectively, as the display unit 43. The display unit 43 can be configured, for example, with an OLED (Organic Light Emitting Diode). The OLED can represent the curved surface of an eyeball, realizing a natural eyeball appearance.

[0040] The display unit 43 displays images of eyes made up of eyeballs, pupils, eyelids, etc. in various states under the control of the control unit 32, thereby enabling a wide range of expressive facial expressions to be realized.

[0041] <Motion Enphasizer>

[0042] FIG. 4 is a diagram for explaining an outline of the motion emphasizer.

[0043] For example, for various robots including articulated robots such as a pet-type robot as the moving body 10 in FIG. 1 , the user of the robot can obtain benefits by giving a certain meaning to the robot's motion. If a robot's motion that can obtain benefits for the user is called a valuable motion, valuable motions include, for example, carrying an object, monitoring a room, and behaving in a cute manner. For a robot to carry an object is beneficial in that it helps the user. For a robot to monitor a room is beneficial in that it makes the user feel at ease. For a robot to behave in a cute manner is beneficial in that it moves the user (makes the user happy).

[0044] With regard to the motions performed by the moving body 10, the creator designs motion data for performing various motions, for example, time-series data of the joint angles of each joint of the moving body 10 when the moving body 10 performs various motions. The motion data designed by the creator is set in the moving body 10 as default data. The moving body 10 performs default motions, which are motions in accordance with the default data, by moving each joint of the moving body 10 in accordance with the default data so that the joint angles become those represented by the default data.

[0045] However, it is difficult for the moving body 10 to express individuality simply by performing default motions in accordance with default data designed by a creator. In other words, if pet-type robots configured similarly to the moving body 10, including the moving body 10, simply perform default motions, for example, to express a certain emotion, all pet-type robots will perform the same motion. In this case, the moving body 10 lacks entertainment value, and it is difficult to develop an attachment to the moving body 10.

[0046] Therefore, the moving object 10 can be made to perform a modified motion, which is a motion that emphasizes or suppresses the default motion, in conjunction with the external situation or internal state of the moving object 10.

[0047] A method of generating modified data, which is motion data for causing the moving body 10 to perform a modified motion, is to use a motion creation tool.

[0048] In the method using a motion creation tool, default data is loaded into the motion creation tool. Then, on the motion creation tool, the creator manipulates the motion waveforms made up of time-series data of the joint angles of each joint as default data, to generate motion waveforms that become modified data.

[0049] The method using a motion creation tool requires the creator to manipulate each and every motion waveform of each joint, which is laborious and time-consuming. Furthermore, a certain level of skill is required to manipulate the motion waveform so that appropriate emphasis or suppression is performed. Therefore, the entry cost is high for non-expert users to generate modified data. Furthermore, simply adjusting the amplitude of the motion waveform to emphasize or suppress the motion may not result in a natural motion to the human eye.

[0050] Therefore, in this technology, modified data is generated using a motion emphasizer. In the motion emphasizer, modified data is generated by inputting default data as motion data of an existing motion to be emphasized or suppressed and several necessary parameters, as shown in Fig. 4. The modified data is motion data that causes the moving object 10 to perform a modified motion that emphasizes or suppresses a default motion in accordance with the default data.

[0051] When a motion enhancer emphasizes or suppresses a motion (default motion), the motion elements (motion elements) that are adjusted include the amplitude, speed, preparatory movement, and swing-back of the motion. The amplitude of the motion is the size of the motion, and for example, in a head-shaking motion, this corresponds to the width of the head swing. The speed of the motion is the speed of the head swing, and for example, in a head-shaking motion, this corresponds to the speed of the head swing or making the head swing faster or slower. The preparatory movement of the motion is an action that is performed just before the original motion to add momentum to the original motion, and for example, in a shaking-hand motion, this corresponds to the action of swinging the hand (foot) up when starting to shake the hand. The swing-back of the motion is an action (overshoot, follow-through) that is performed immediately after the original motion with excess momentum, and for example, in a shaking-hand motion, this corresponds to the action of slamming the hand (foot) down immediately after shaking the hand.

[0052] According to the Motion Emphasizer, by inputting default data and a few necessary parameters, modified data for modified motion that emphasizes or suppresses the default motion is generated. Therefore, not only experienced creators but also inexperienced users can easily generate modified data for performing modified motion, that is, they can generate modified data without much effort or time. Furthermore, the entry cost for beginners and other inexperienced users to start generating modified data can be reduced.

[0053] Furthermore, the motion enhancer generates modified data for modified motions in which the amplitude, speed, preparatory movement, and swing-back of the default motion are appropriately and continuously adjusted. Therefore, modified data for performing natural motions can be generated. For example, it is possible to generate modified data for performing motions with speeds that could not be generated by simply adjusting the amplitude.

[0054] As described above, the entertainment value of the moving object 10 can be improved by having the moving object 10 perform modified motions, which are motions that emphasize or suppress default motions in conjunction with external circumstances or internal states. Furthermore, by using a motion emphasizer to generate modified data that causes the moving object 10 to perform modified motions, the modified data can be easily generated. As a result, the entertainment value of the moving object 10 can be easily improved.

[0055] <Cartoon animation filter>

[0056] FIG. 5 is a diagram illustrating a cartoon animation filter.

[0057] The method used by the motion enhancer to generate modified data for modified motion that emphasizes or suppresses default motion is based on the cartoon animation filter described in Jue Wang, Steven M. Drucker, Maneesh Agrawala, and Michael F. Cohen, "The cartoon animation filter," ACM Transactions on Graphics, Volume 25, Issue 3, pp. 1169-1173, Published: July 1, 2006.

[0058] In the cartoon animation filter, if time is represented by t and default data is represented by x(t), a Laplacian of Gaussian (LoG) filter is applied to the default data x(t). The filtering result of the LoG filter, -Δx*(t), is then added to the default data x(t) to generate enhanced motion data x*(t) that emphasizes the default motion.

[0059] In the equations shown in Figure 5, a cross within a circle represents convolution (product-sum operation), and LoG represents the LoG filter (as a kernel). Furthermore, A is a predetermined constant, Δt represents a predetermined time interval, σ represents a predetermined standard deviation, and x''(t) represents the second derivative of x(t). As shown in Figure 5, applying the LoG filter to default data x(t) is equivalent to convolving the second derivative x''(t) of the default data x(t) with A·exp(-(t / σ±Δt)^2) as the kernel.

[0060] The cartoon animation filter, through the simple process of applying an LoG filter, can create an eye-catching effect through preparatory movements and emphasize motion by increasing the amount of movement, as shown in the dotted oval in Figure 5. The cartoon animation filter is relatively easy to implement and verify, requires little computation, and can be easily implemented in real time.

[0061] The motion emphasizer generates modified data for modified motion that easily conveys emotions, intentions, etc., based on the method for generating motion data x*(t) for emphasized motion in the cartoon animation filter.

[0062] <Generation of Emphasized Motion Data>

[0063] FIG. 6 is a diagram for explaining the generation of modified data (emphasized motion data) for performing an emphasized motion by emphasizing the default motion in the motion emphasizer.

[0064] The motion emphasizer receives input of default data (as motion data) and a parameter file. The default data is, for example, time-series data in CSV (comma separated values) format of the joint angles of each joint of the moving body 10 when the moving body 10 performs a default motion according to the default data. The parameter file stores information indicating whether the default motion is emphasized or suppressed depending on the user's operation, etc., as well as an additive coefficient a(t), which will be described later, as parameters for generating modified data.

[0065] In the motion emphasizer, in response to input of default data and a parameter file, for example, emphasis motion data that causes the moving body 10 to perform an emphasis motion that emphasizes the default motion in accordance with the default data is generated as modified data. The emphasis motion data as modified data is data similar to the default data, for example, time-series data in CSV format of the joint angles of each joint of the moving body 10 when the moving body 10 performs an emphasis motion in accordance with the emphasis motion data.

[0066] In generating emphasized motion data as modified data, the motion emphasizer generates an emphasized component e(t). The emphasized component e(t) is a component for emphasizing the default motion, and is generated using the default data d(t). By adding the emphasized component e(t) to the default data d(t), emphasized motion data is generated as modified data m(t).

[0067] For example, in a motion enhancer, an emphasis component e(t) is generated by applying an LoG filter to default data d(t). Then, the emphasis component e(t) is used to generate (calculate) emphasized motion data as modified data m(t) according to, for example, the formula m(t) = d(t) + E e(t) a(t).

[0068] In the formula m(t) = d(t) + E e(t) a(t), the emphasis coefficient E is a coefficient (constant value) that adjusts the degree of emphasis by the emphasis component e(t) in order to limit the emphasis motion. The emphasis coefficient E can take on a different value for each joint, for example. The addition coefficient a(t) is a coefficient that adjusts the interval in which the emphasis component e(t) is added to the default data d(t). The addition coefficient a(t) can be stored as a parameter in a parameter file. The emphasis coefficient E and the addition coefficient a(t) can be applied not only to generating emphasis motion data that causes the moving body 10 to perform emphasis motion that emphasizes the default motion, but also to generating suppression motion data that causes the moving body 10 to perform suppression motion that suppresses the default motion.

[0069] In Fig. 6, emphasis motion data is generated as modified data m(t) with a(t) = 1. In Fig. 6, it can be seen that the emphasis motion based on the emphasis motion data as modified data m(t) has a larger amplitude than the default motion based on the default data d(t), and that a preparatory movement and swing-back are added.

[0070] FIG. 7 is a diagram illustrating the emphasis coefficient E. In FIG.

[0071] In a motion emphasizer, if emphasized motion data is generated as modified data m(t) by simply adding the emphasized component e(t) to the default data d(t), the emphasized motion data may exceed the range of motion. For example, the joint angle in the emphasized motion data may exceed the range of motion of the joint (joint angle), as shown by the shading in Figure 7.

[0072] If the joint angle of the emphasized motion data exceeds the range of motion of the joint, there is a risk that the moving body 10 will be damaged if the joint of the moving body 10 is moved in accordance with such emphasized motion data.

[0073] Therefore, in the motion enhancer, emphasized motion data is generated as modified data m(t) according to the formula m(t) = d(t) + E e(t) a(t), which uses an emphasis coefficient E that adjusts the degree of emphasis by the emphasis component e(t). In generating the modified data m(t) according to the formula m(t) = d(t) + E e(t) a(t), the emphasis coefficient E is set so that the modified data m(t) at each time t falls within the range of motion of the joints of the moving body 10.

[0074] For simplicity, let us assume that a(t) = 1. In the motion enhancer, modified data m(t) is generated for each time t according to the formula m(t) = d(t) + E·e(t)·a(t), while setting the emphasis coefficient E so that the modified data m(t) falls within the range of motion. For example, the motion enhancer calculates modified data m(t) for each time t according to the formula m(t) = d(t) + e(t)·a(t), which does not use the emphasis coefficient E (i.e., the emphasis coefficient E = 1). Furthermore, for modified data m(t) that exceeds the limit of the range of motion, when the motion enhancer calculates the modified data m(t) according to the formula m(t) = d(t) + E·e(t)·a(t), an emphasis coefficient E that is within the range of motion, for example, the limit of the range of motion, is calculated. The limits of the range of motion refer to, for example, the maximum and minimum values ​​of the joint angle of the range of motion. "Exceeding the limits of the range of motion" and "exceeding the range of motion" have the same meaning, and refer to, for example, being greater than the maximum value of the joint angle of the range of motion or being smaller than the minimum value of the joint angle of the range of motion.

[0075] In the motion emphasizer, the smallest emphasis coefficient (hereinafter also referred to as the minimum coefficient) among the emphasis coefficients E at each time t calculated as described above, or a value less than the minimum coefficient, is set as the final emphasis coefficient E when calculating modified data m(t) according to the formula m(t) = d(t) + E e(t) a(t). Then, the modified data m(t) is calculated according to the formula m(t) = d(t) + E e(t) a(t) using the final emphasis coefficient E.

[0076] As described above, modified data m(t) is calculated according to the formula m(t) = d(t) + E e(t) a(t) using the final emphasis coefficient E, thereby preventing modified data m(t) that exceeds the range of motion from being generated, thereby preventing damage to the moving body 10.

[0077] It should be noted that, for example, since the range of motion may differ for each joint in the moving body 10, the emphasis coefficient E can be set for each joint. The range of motion can be stored as a parameter in a parameter file.

[0078] FIG. 8 is a diagram illustrating a first example of the limiting coefficient.

[0079] The limiting coefficient is a coefficient for limiting the emphasis motion, and in that it is such a coefficient, it is similar to the emphasis coefficient E. However, the emphasis coefficient E is a coefficient that adjusts (limits) the degree of emphasis by the emphasis component e(t) in order to limit the emphasis motion. In contrast, the limiting coefficient is a coefficient that adjusts (limits) the emphasis motion data itself as modified data m(t) in order to limit the emphasis motion. As described above, the limiting coefficient differs from the emphasis coefficient E that adjusts the degree of emphasis by the emphasis component e(t) in that it is a coefficient that adjusts the emphasis motion data itself as modified data m(t).

[0080] In the motion emphasizer, the emphasized motion data as modified data m(t) can be converted using a limiting coefficient so that it fits within the range of motion of the moving object 10.

[0081] For example, if the maximum value of the magnitude of the emphasized motion data as modified data m(t) calculated according to the formula m(t) = d(t) + e(t) a(t) (or the formula m(t) = d(t) + E e(t) a(t) where E is fixed to a predetermined value) is represented as W and the limit value of the range of motion is represented as L, then the limit coefficient can be, for example, L / W. Then, the motion enhancer can convert the modified data m(t) into converted data n(t) obtained by multiplying the modified data m(t) by the limit coefficient L / W according to the formula n(t) = L / W m(t) + C. In this case, the control unit 32 ( FIG. 2 ) causes the moving object 10 to perform a motion according to the converted data n(t). The coefficient C in the formula n(t) = L / W m(t) + C is a predetermined constant, for example, 0.

[0082] For example, rotation of a joint around a certain axis can be either counterclockwise rotation around that axis or clockwise rotation in the opposite direction. Furthermore, with the joint angle of a joint in a certain rotational state set at 0 degrees as a reference angle, the joint can rotate either counterclockwise or clockwise from the reference angle. If counterclockwise rotation is referred to as positive rotation and clockwise rotation as negative rotation, the limit values ​​of the range of motion may differ between positive and negative rotation.

[0083] Let us now represent the rotation angles of positive and negative rotations as positive and negative values, respectively. Furthermore, let us represent the limits of the range of motion (magnitude of the range of motion) of positive and negative rotations as L1 and L2, respectively, and let us represent the maximum magnitudes of the positive and negative rotation angles in the emphasized motion data as modified data m(t) as W1 and W2, respectively.

[0084] In this case, positive rotation angles of the modified data m(t) are converted to transformed data n(t) according to the formula n(t) = L1 / W1 m(t) + C, using L1 / W1 as the limiting coefficient L / W. Negative rotation angles of the modified data m(t) are converted to transformed data n(t) according to the formula n(t) = L2 / W2 m(t) + C, using L2 / W2 as the limiting coefficient L / W.

[0085] According to the limit coefficient L / W, the modified data m(t) is, so to speak, normalized to a value within the range of motion and limited to a value within the range of motion. That is, the modified data m(t) is converted into converted data n(t) by multiplying the modified data m(t) by the limit coefficient L / W. Therefore, the converted data n(t) contains an emphasized component e(t) multiplied by the limit coefficient L / W, and becomes time-series data having a smooth waveform similar to that of the modified data m(t). Furthermore, because the converted data n(t) has a value within the range of motion, it is possible to prevent damage to the operating body 10 caused by modified data m(t) that exceeds the range of motion.

[0086] FIG. 9 is a diagram illustrating a second example of the limiting coefficient.

[0087] 8, a fixed limiting factor L / W is used for each of positive and negative rotations to linearly convert the modified data m(t) into converted data n(t) that is multiplied by the limiting factor L / W of the modified data m(t).In addition to the fixed limiting factor L / W, a function f(m(t)) whose value changes depending on the modified data m(t) can also be used as the limiting factor.

[0088] When the function f(m(t)) is used as the limiting coefficient, the motion enhancer can nonlinearly convert the modified data m(t) into converted data n(t) obtained by multiplying the modified data m(t) by the limiting coefficient f(m(t)) according to the formula n(t) = f(m(t)) m(t) + C.

[0089] The function f(m(t)) used as the limiting coefficient can be a function that, so to speak, limits (increases the degree of limiting) the modified data m(t) that is near or exceeds the limit value of the range of motion. For example, the function f(m(t)) used as the limiting coefficient can be a function that has a value of 1 when the modified data m(t) is near the reference angle of 0 degrees, smoothly decreases toward the maximum value W1 and the minimum value W2 of the modified data m(t), and limits the converted data n(t) to the maximum value L1 and the minimum value -L2, respectively, as the limit values ​​of the range of motion, at (or above) the maximum value W1 and at (or below) the minimum value -W2.

[0090] According to the function f(m(t)) as the limiting coefficient, the modified data m(t) is nonlinearly transformed so that the larger modified data m(t) is more limited (adjusted to a greater degree of limitation) than the smaller modified data m(t), as shown in FIG. 9 .

[0091] FIG. 10 is a diagram illustrating an example of setting the emphasis coefficient E for each joint.

[0092] When emphasizing a certain default motion, if the movement of the joints that move when performing that default motion is uniformly emphasized, the emphasized motion may become unnatural. For example, an emphasized motion may be created that completely fails to convey the intention that the default motion is trying to convey.

[0093] Therefore, the degree to which the default motion is emphasized by the emphasis component e(t) can be adjusted for each joint so that the emphasized motion does not appear unnatural.

[0094] The degree of emphasis by the emphasis component e(t) for each joint can be adjusted by, for example, setting an emphasis coefficient E for each joint.

[0095] For example, in the motion enhancer, when generating emphasized motion data as modified data m(t) according to the formula m(t) = d(t) + E e(t) a(t) using the emphasis coefficient E, a value equal to or less than the minimum coefficient (the minimum coefficient or a value less than the minimum coefficient) can be set as the final emphasis coefficient E, as described in Fig. 7. The final emphasis coefficient E can be set for each joint.

[0096] 10, the emphasis coefficient E1 is set as the final emphasis coefficient E for the neck joints, and the emphasis coefficient E2 is set as the final emphasis coefficient E for the foot joints, and the modified data m(t) is calculated according to the formula m(t) = d(t) + E e(t) a(t). The emphasis coefficients E1 and E2 have a relationship expressed by the formula E1 > E2. Therefore, the degree of emphasis is high for the neck joints, and low for the foot joints.

[0097] As described above, by setting the emphasis coefficient E for each joint, it is possible to prevent the emphasis motion from becoming unnatural. Information on the degree of emphasis by the emphasis component e(t) for each joint, which is used to set the emphasis coefficient E for each joint, can be stored as a parameter in a parameter file.

[0098] FIG. 11 is a diagram illustrating the addition coefficient a(t).

[0099] In a motion emphasizer, when generating emphasized motion data as modified data m(t) according to the formula m(t) = d(t) + E·e(t)·a(t), the addition coefficient a(t) can be used to add the emphasis component e(t) to adjust the addition section, which is the section in which the default motion is emphasized.

[0100] FIG. 11 shows an example of default data d(t), emphasis component e(t), and addition coefficient a(t), as well as modified data m(t) = d(t) + E e(t) a(t) generated using the default data d(t), emphasis component e(t), and addition coefficient a(t).

[0101] In the addition interval, the addition coefficient a(t) can be set to a value near 1, for example, and in the interval that is not the addition interval, the addition coefficient a(t) can be set to a value near 0, for example.

[0102] Regarding the additive coefficient a(t), for example, one or more values ​​that become the additive coefficient a(t) can be stored as parameters in a parameter file, and the additive coefficient a(t) for each time t can be set (generated) by performing interpolation or the like using the one or more values ​​as parameters.

[0103] Furthermore, the addition coefficient a(t) can be used to adjust the addition interval as well as the degree of emphasis by the emphasis component e(t) in each interval. In this case, the addition coefficient a(t) is not set using a parameter value stored in a parameter file, but can be set based on the modified data m(t) generated according to the formula m(t) = d(t) + E e(t) without using the addition coefficient a(t) (a(t) = 1), or on external conditions, etc.

[0104] For example, in a section where the speed of the actuator exceeds a certain value when moving a joint in accordance with modified data m(t) generated according to the formula m(t) = d(t) + E·e(t), a small value can be set as the additive coefficient a(t) so as to reduce the degree of emphasis by the emphasis component e(t) from the viewpoint of preventing damage to the moving body 10. Also, in a section where the joint angle is near the limit of the range of motion when moving a joint in accordance with modified data m(t) generated according to the formula m(t) = d(t) + E·e(t), a small value can be set as the additive coefficient a(t) so as to reduce the degree of emphasis by the emphasis component e(t). Movement of a joint where the joint angle is near the limit of the range of motion is likely to be unnatural, so unnatural movement can be suppressed by reducing the degree of emphasis by the emphasis component e(t) in a section where the joint angle is near the limit of the range of motion.

[0105] Furthermore, for example, when the external situation recognized based on the sensor information is recognized by image recognition or voice recognition as being that the master is nearby or that the master has called out to the user, a large value can be set as the additive coefficient a(t) so as to increase the degree of emphasis by the emphasis component e(t). Also, when the external situation recognized based on the sensor information is recognized by image recognition or voice recognition as being that a person other than the master is nearby or that a person other than the master has called out to the user, a small value can be set as the additive coefficient a(t) so as to decrease the degree of emphasis by the emphasis component e(t).

[0106] <Processing repeat parts>

[0107] FIG. 12 is a diagram for explaining the inconvenience of modified data occurring in a repeat portion.

[0108] The default data can have a repeatable repeat portion (time-series data). The portion of the default data other than the repeat portion is referred to as a non-repeat portion. For the repeat portion, the control unit 32 can cause the moving object 10 to perform a motion according to the time-series data in which the repeat portion is repeated the number of times indicated by information accompanying the repeat portion as overhead.

[0109] The repeat portion is designed so that when the repeat portion is repeated, a continuous and smooth waveform is obtained, as shown in Fig. 12. This allows the moving body 10 to perform a smooth motion during the repetition of the repeat portion.

[0110] As described above, the repeat portions of default data are designed to produce a continuous and smooth waveform when repeated. However, modified data in which the repeat portions of such default data are emphasized or suppressed does not necessarily produce a continuous and smooth waveform when repeated. In other words, if time series data in which the repeat portions of default data d(t) are emphasized or suppressed is used as the repeat portion of modified data m(t), when the repeat portion of modified data m(t) is repeated, the waveform of the repeated portion may be unsmooth or discontinuous, as shown in FIG. 12.

[0111] If the repeated waveform of the repeat portion is not smooth or is discontinuous, the motion of the moving body 10 will be unnatural, and there is a risk that the moving body 10 may be damaged.

[0112] Therefore, in the Motion Emphasizer, the repeat portion of the modified data is generated as follows.

[0113] FIG. 13 is a diagram for explaining the generation of a repeat portion of modified data.

[0114] In the motion emphasizer, as shown in A of FIG. 13, repeat default data is generated, which is time-series data in which the repeat portion of the default data is repeated.

[0115] In the motion emphasizer, modified data for the repeat default data is generated using the repeat default data, as shown in B of Fig. 13. That is, the repeat modified data is generated by emphasizing or suppressing the repeat default data. Since the repeat default data has a continuous and smooth waveform, the repeat modified data for such repeat default data also has a continuous and smooth waveform.

[0116] The Motion Enphasizer uses non-repeating portions that connect (adjacent) to repeating portions of the default data to generate modified data for the non-repeating portions.

[0117] In the motion emphasizer, interpolation is performed to smoothly connect the modified data for the non-repeat portions of the default data with the repeat modified data, as shown in C of Fig. 13. Then, the motion emphasizer uses the data obtained by the interpolation to generate the repeat and non-repeat portions of the modified data for the repeat and non-repeat portions of the default data.

[0118] For non-repeat portions of the modified data, the control unit 32 causes the moving object 10 to perform a motion in accordance with the time-series data of the non-repeat portions. For repeat portions of the modified data, the control unit 32 causes the moving object 10 to perform a motion in accordance with the time-series data in which the repeat portion of the modified data is repeated the number of times indicated by information accompanying the repeat portion of the default data as overhead.

[0119] The repeat and non-repeat portions of the modified data are smoothly connected by interpolation. Furthermore, the repeat modified data obtained by repeating the repeat portions of the modified data has a continuous and smooth waveform, as described above. Therefore, the time-series data as modified data used by the control unit 32 to cause the moving object 10 to perform a movement has a continuous and smooth waveform, which prevents the motion of the moving object 10 from becoming unnatural and prevents damage to the moving object 10, as described in FIG. 12.

[0120] <Generation of suppression motion data>

[0121] FIG. 14 is a diagram for explaining the generation of modified data (suppressed motion data) for performing suppressed motion by suppressing default motion in the motion emphasizer.

[0122] In the motion emphasizer, in response to input of default data and a parameter file, for example, suppressed motion data that causes a suppressed motion that suppresses the default motion according to the default data can be generated as modified data.

[0123] For example, the motion enhancer can generate (calculate) suppressed motion data as modified data m(t) according to the formula m(t) = (1-k) d(t) + k d2(t), which performs a weighted addition of default data d(t) and the second-order derivative d2(t) of the default data d(t). For example, the motion enhancer can generate the second-order derivative d2(t) of the default data d(t) by applying an LoG filter to the default data d(t). In the formula m(t) = (1-k) d(t) + k d2(t), k is the weight for the weighted addition and can be stored as a parameter in a parameter file. Furthermore, the weight k for each joint can be stored in the parameter file.

[0124] As described above, the emphasis coefficient E and the addition coefficient a(t) can be applied to generate suppression motion data. When the emphasis coefficient E and the addition coefficient a(t) are applied to generate suppression motion data, for example, the emphasis coefficient E and the addition coefficient a(t) are multiplied by the second derivative d2(t) of the default data.

[0125] By generating suppression motion data as modified data m(t) according to the formula m(t) = (1-k) d(t) + k d2(t), which performs a weighted addition of default data d(t) and the second derivative d2(t) of that default data d(t), it is possible to generate suppression motion data that is not simply time series data in which the amplitude of the default data d(t) is suppressed, but time series data in which a suppression motion is performed that includes a preparatory movement due to the influence of the second derivative d2(t) of the default data d(t).

[0126] Here, in a suppression motion performed according to time-series data in which the amplitude of the default data d(t) is simply suppressed, the movement of each joint is merely reduced, which may make it difficult for the user to understand the intention of the suppression motion, etc. In contrast, as described above, in a suppression motion that includes a preparatory movement, the degree to which it becomes difficult for the user to understand the intention of the suppression motion, etc. can be reduced by the preparatory movement.

[0127] The control unit 32 can control the moving body 10 to perform a suppressing motion in conjunction with the external situation of the moving body 10 and / or the internal situation of the moving body 10, for example, when the remaining battery charge is low as an internal situation, when the moving body 10 has a shy personality as an internal situation, when the bpm (beats per minute) of music being played in the surroundings or applause is high as an external situation, etc. This can broaden the range of expression achieved by the motion of the moving body 10.

[0128] <Adding emphasis to the tempo>

[0129] FIG. 15 is a diagram for explaining the generation of modified data (emphasized motion data) for performing emphasized motion by adding speed and velocity to default motion in the motion emphasizer.

[0130] To emphasize the default motion, the default motion can be varied in speed.

[0131] For example, the motion enhancer can generate enhanced motion data as modified data m(t) that enhances the default motion by adding weights to the default data d(t) and the odd-numbered power d(t)^(2i+1) (i = 0, 1, ...) according to the formula m(t) = (1-k) d(t) + k d(t)^(2i+1). The odd-numbered power d(t)^(2i+1) of the default data d(t) can be, for example, the seventh power d(t)^7. The exponent 2i+1 of the odd-numbered power d(t)^(2i+1) can be stored as a parameter in a parameter file. In the formula m(t) = (1-k) d(t) + k d(t)^(2i+1), k is the weight for the weighted addition and can be stored as a parameter in a parameter file. Furthermore, the weight k for each joint can be stored in the parameter file.

[0132] A waveform formed by the odd power d(t)^(2i+1) of the default data d(t) is a waveform containing high-frequency components, similar to a waveform formed by increasing the frequency of the default data d(t). Therefore, by generating emphasized motion data as modified data m(t) according to the formula m(t) = (1-k) d(t) + k d(t)^(2i+1), which performs a weighted addition of the default data d(t) and the odd power d(t)^(2i+1) of the default data d(t), it is possible to generate time-series data as emphasized motion data in which some movements in the default motion are made faster, resulting in emphasized motion with varying speeds.

[0133] The control unit 32 can control the moving body 10 to perform an emphatic motion with varying speed in conjunction with the external situation of the moving body 10 and / or the internal state of the moving body 10, for example, in conjunction with an external situation such as a low bpm of music being played in the surroundings or applause, an internal state such as a low remaining battery charge, or a shy personality, etc. This can broaden the range of expression possible through the motion of the moving body 10.

[0134] <Motion example>

[0135] FIG. 16 is a diagram showing examples of default motion and enhanced motion (modified motion) that enhances the default motion.

[0136] In Fig. 16, the dog-shaped moving body 10 is standing on all fours and performing a dance motion in which it sways its body, including its head, up and down. Fig. 16 shows a dance motion as a default motion and an emphasis motion that emphasizes the default motion.

[0137] In the emphasized motion, the head movement, mouth opening, and leg bending when crouching are all increased compared to the default motion, which confirms that the default motion is emphasized in a natural way.

[0138] FIG. 17 is a diagram showing an example of a default motion and a suppressed motion (modified motion) obtained by suppressing the default motion.

[0139] In Fig. 17, the dog-shaped moving body 10 is standing on all fours, performing a dance motion in which it sways its body, including its head, up and down, similar to Fig. 16. Fig. 17 shows a dance motion as a default motion and a dance motion as a suppressed motion that suppresses the default motion. The dance motion as the default motion in Fig. 17 is the same as that in Fig. 16.

[0140] In the suppressed motion, the range of head movement, the opening of the mouth, and the degree to which the legs bend when the robot assumes a crouching position are all reduced compared to the default motion, which confirms that the default motion has been suppressed to a natural form.

[0141] The moving body 10 performs an emphasis motion or a suppression motion that emphasizes or suppresses the default motion in conjunction with the external situation and / or the internal state, so that the emphasis motion, the suppression motion, or the default motion is performed depending on the external situation and the internal state. Therefore, a wide variety of motions that differ depending on the external situation and the internal state are performed, allowing the user to feel that the moving body 10's motions are rich in expression.

[0142] <Processing of the operating body 10>

[0143] FIG. 18 is a flowchart illustrating an example of processing by the operating body 10.

[0144] In the moving object 10 (FIG. 2), in step S11, the trigger detection unit 31 determines whether a motion event has been detected based on the sensor information from the sensor device 21 and / or the internal state information from the control unit 32.

[0145] If it is determined in step S11 that a motion event has not been detected, the process returns to step S11, and the process of step S11 is repeated.

[0146] If it is determined in step S11 that a motion event has been detected, the trigger detection unit 31 supplies motion information representing the motion corresponding to the motion event to the control unit 32, and the process proceeds to step S12.

[0147] In step S12, the control unit 32 controls the moving body 10 in conjunction with the external situation and / or internal state of the moving body 10 to perform a motion represented by the motion information from the trigger detection unit 31, i.e., a motion that emphasizes or suppresses the default motion corresponding to the motion event detected by the trigger detection unit 31.

[0148] In step S12, first, in step S21, the control unit 32 recognizes the external situation of the moving body 10 based on sensor information from the sensor device 21 and / or obtains internal state information by reading it from the built-in memory, and the processing proceeds to step S22.

[0149] In step S22, the control unit 32 uses the default data of the default motion corresponding to the motion event to generate modified data that causes the motion to be enhanced or suppressed in response to the external situation of the moving object 10 and / or the internal state of the moving object 10 represented by the internal state information. The control unit 32 can generate the modified data by inputting the default data to a motion emphasizer, for example, by calling a function serving as the motion emphasizer using the default data as an argument.

[0150] Although the modified data is generated in the control unit 32 here, the modified data can be generated in advance on a server or the like, downloaded to the moving body 10, and stored in the built-in memory. In this case, in step S22, the control unit 32 reads from the built-in memory modified data that causes the moving body 10 to perform a motion that emphasizes or suppresses the default motion corresponding to the motion event, in conjunction with the external situation of the moving body 10 and / or the internal state of the moving body 10 represented by the internal state information.

[0151] After step S22, the process proceeds to step S23, where the control unit 32 causes the moving object 10 to perform a motion in accordance with the modified data.

[0152] FIG. 19 is a flowchart illustrating an example of processing performed by the moving body 10 performing a dance motion in time with clapping or music.

[0153] Figure 19 shows the processing of the moving body 10 when, for example, a motion event such as clapping or music being played corresponds to a dance motion of a speed that matches the bpm of the clapping or music, and an emphasis motion or suppression motion that emphasizes or suppresses the dance motion is performed.

[0154] In the moving object 10 (FIG. 2), in step S31, the trigger detection unit 31 determines whether clapping or music has been detected as a motion event, based on sensor information from the sensor device 21. Step S31 corresponds to step S11 in FIG.

[0155] If it is determined in step S31 that a motion event has not been detected, the process returns to step S31, and the process of step S31 is repeated.

[0156] If it is determined in step S31 that a motion event, i.e., in this case, clapping or music, has been detected, the trigger detection unit 31 supplies motion information representing the motion corresponding to the motion event to the control unit 32, and processing proceeds to step S32.

[0157] In step S32, the control unit 32 controls the moving object 10 to perform a motion that emphasizes or suppresses the dance motion as the default motion corresponding to the motion event of clapping or music, i.e., the motion represented by the motion information from the trigger detection unit 31, in conjunction with the bpm of clapping or music as the external situation of the moving object. Step S32 corresponds to step S12 in Fig. 18 .

[0158] In step S32, first, in step S41, the control unit 32 determines whether clapping or music is being played based on the sensor information from the sensor device 21.

[0159] If it is determined in step S41 that clapping or music is occurring (continuing to occur), the process proceeds to step S42.

[0160] In step S42, the control unit 32 recognizes the bpm of clapping or music as the external situation of the moving object 10 based on the sensor information from the sensor device 21, and the process proceeds to step S43. Step S42 corresponds to step S21 in FIG. 18.

[0161] In step S43, the control unit 32 uses the default data of the dance motion to generate modified data that causes the dance motion as the default motion to be emphasized or suppressed in conjunction with the bpm of the clapping or music.

[0162] For example, if the bpm of the clapping or music is low, i.e., if the bpm of the clapping or music is less than the first threshold TL (bpm<TL), the control unit 32 generates modified data that emphasizes the dance motion as the default motion and performs an emphasized motion. For example, if the bpm of the clapping or music is medium, i.e., if the bpm of the clapping or music is equal to or greater than the first threshold TL and less than the second threshold TH (TL<=bpm<TH), the control unit 32 uses the default data that performs the dance motion as the default motion as modified data. For example, if the bpm of the clapping or music is high, i.e., if the bpm of the clapping or music is equal to or greater than the second threshold TH (TH<=bpm), the control unit 32 generates modified data that suppresses the dance motion as the default motion and performs a suppressed motion.

[0163] Step S43 corresponds to step S22 in FIG. 18. Therefore, in step S43, similar to step S22, modified data for an emphasized motion or a suppressed motion can be generated by inputting default data into the motion emphasizer. Also, in step S43, the modified data is not generated by the control unit 32, but can be generated in advance by a server or the like, downloaded to the moving body 10, and stored in the built-in memory. In this case, in step S43, the control unit 32 reads from the built-in memory modified data that causes a motion in which the dance motion as the default motion is emphasized or suppressed in conjunction with the bpm of the handclaps or music.

[0164] After step S43, the process proceeds to step S44, where the control unit 32 causes the moving body 10 to perform a motion in accordance with the modified data. For example, the control unit 32 time-stretches the modified data, and causes the moving body 10 to perform a modified motion for four or eight bars in accordance with the modified data after time stretching. Step S44 corresponds to step S23 in FIG. 18.

[0165] After step S44, the process returns to step S41, where it is determined whether clapping or music is occurring, as described above. If it is determined in step S41 that clapping or music is no longer occurring (has stopped), the process ends.

[0166] FIG. 20 is a diagram showing an example of a motion performed by the moving object 10 through the processing of FIG.

[0167] FIG. 20 shows examples of default motions, dance motions whose speed matches the bpm of handclaps or music, and emphasis motions that emphasize the default dance motions.

[0168] In Fig. 20, the dog-shaped moving body 10 is performing a dance motion in which it lies on its stomach, sways its head from side to side, and raises and lowers its front legs. Fig. 20 shows a default motion, which is a dance motion performed when the bpm of the clapping or music is medium. Fig. 20 also shows an emphasized motion that emphasizes the dance motion as the default motion, which is performed when the bpm of the clapping or music is low.

[0169] When the bpm of the claps or music is medium, the dance motion as a default motion with a speed that matches the bpm of the claps or music moves the moving body 10 at a certain speed, so the dance appears to match the beat of the claps or music. However, when the bpm of the claps or music is low, the dance motion as a default motion with a speed that matches the bpm of the claps or music moves the moving body 10 slowly, so the movement appears flat (smooth) and gives the impression of being redundant.

[0170] Therefore, when the bpm of the applause or music is low, as explained in Figure 19, the moving body 10 is made to perform an emphasis motion that emphasizes a dance motion as a default motion at a speed that matches the bpm of the applause or music.

[0171] In this way, by making the moving body 10 perform an emphasis motion at low bpm, the head sway width and the front legs raised become larger compared to the default motion, as shown in Fig. 20, and the movement of the moving body 10 becomes slow but dynamic. As a result, like the dance motion as the default motion at low bpm, the movement of the moving body 10 becomes flat and the impression of being redundant can be prevented.

[0172] FIG. 21 is a diagram showing an example of a motion performed by the moving object 10 through the processing of FIG.

[0173] FIG. 21 is a diagram showing an example of a default motion, which is a dance motion with a speed that matches the bpm of handclaps or music, and a suppressed motion that suppresses the default dance motion.

[0174] In Fig. 21, the dog-type moving body 10 is performing a dance motion in which it is lying on its stomach, swaying its head from side to side, and raising and lowering its front legs, similar to Fig. 20. Fig. 21 shows a default motion, which is a dance motion performed when the bpm of the clapping or music is medium. Fig. 21 also shows a suppressed motion, which is a suppressed version of the default dance motion, performed when the bpm of the clapping or music is high. The default dance motion in Fig. 21 is the same as that in Fig. 20.

[0175] As explained in Fig. 20, when the bpm of the clapping or music is medium, the dance motion as the default motion with a speed that matches the bpm of the clapping or music moves the moving body 10 at a certain speed, so that the dance appears to match the beat of the clapping or music. However, when the bpm of the clapping or music is high, the dance motion as the default motion with a speed that matches the bpm of the clapping or music moves the moving body 10 faster, so that the movement appears jerky and gives the impression of being hectic.

[0176] Therefore, when the bpm of the applause or music is high, as explained in Figure 19, the moving body 10 is made to perform a suppressed motion that suppresses the dance motion as a default motion with a speed that matches the bpm of the applause or music.

[0177] In this way, by making the moving body 10 perform a suppressed motion at high bpm, the head sway width and the degree to which the front legs are raised become smaller compared to the default motion, and the movement of the moving body 10 becomes fast but rhythmic, as shown in Fig. 21. As a result, it is possible to prevent the movement of the moving body 10 from becoming jerky, like the dance motion that is the default motion at high bpm, and from giving the impression of being hectic.

[0178] <External and internal conditions>

[0179] FIG. 22 is a diagram illustrating an example of an external situation, an internal state, and a motion performed in conjunction with the external situation or the internal state.

[0180] When the moving body 10 detects a motion event, it performs a motion corresponding to the motion event. At that time, the moving body 10 performs an emphasized motion or a suppressed motion that emphasizes or suppresses the motion corresponding to the motion event (default motion) in conjunction with the external situation (external factor) of the moving body 10 and / or the internal state (internal factor) of the moving body 10.

[0181] Examples of external situations include a situation where a loud noise is heard or a situation where a person that the robot dislikes is within its field of vision. The operating body 10 can perform (execute) a suppression motion in conjunction with such external situations. Examples of external situations include a situation where a friend is nearby, a situation where a master is within its field of vision, a situation where the room is bright, or a situation where something that the robot likes is within its field of vision. The operating body 10 can perform (execute) an emphasis motion in conjunction with such external situations.

[0182] The internal state may be, for example, when the body is hot, when the battery is low, or when some part of the body is broken. The moving body 10 can perform a suppression motion in conjunction with such an internal state. The internal state may also be, for example, when the battery has just been fully charged, when the body is in good health after eating food, or when the body is able to grasp something well. The moving body 10 can perform an emphasis motion in conjunction with such an internal state.

[0183] In addition, the moving body 10 can perform an emphasis motion or suppression motion that emphasizes or suppresses a motion (default motion) corresponding to a motion event in conjunction with both the external situation and the internal state.

[0184] For example, the moving object 10 can perform a suppression motion with a greater degree of suppression in response to both an external situation in which a loud noise has occurred and an internal state in which the battery is low. For example, the moving object 10 can be made to perform a (suppression) motion in accordance with suppression motion data as modified data m(t) generated by setting the weight k in the equation m(t) = (1 - k) d(t) + k d2(t) described in Fig. 14 to a value greater than that in the case in which either an external situation in which a loud noise has occurred or an internal state in which the battery is low occurs alone.

[0185] Furthermore, for example, the operating body 10 can perform an emphasis motion with a greater degree of emphasis in conjunction with both the external situation of having a companion nearby and the internal state of being healthy after eating food. For example, the operating body 10 can be made to perform an (emphasis) motion in accordance with emphasis motion data as modified data m(t) generated by setting the emphasis coefficient E in the equation m(t) = d(t) + E e(t) a(t) described in Fig. 6 to a value greater than the external situation of having a companion nearby or the internal state of being healthy after eating food alone.

[0186] FIG. 23 is a diagram illustrating an example of an external situation and a manner in which a motion is emphasized or suppressed in conjunction with the external situation.

[0187] For example, in response to an external situation where a loud noise is heard, it is possible to emphasize increasing the size of trembling motions or suppress overall motion reduction. For example, in response to an external situation where a disliked person is within the field of view, it is possible to emphasize increasing the size of growling motions, barking motions, or sad meowing motions. For example, in response to an external situation where a room is dark, it is possible to suppress overall motion reduction. For example, in response to an external situation where a companion is nearby, it is possible to emphasize increasing the size of joy motions that express joy or friendly motions that show friendliness. For example, in response to an external situation where a master is within the field of view, it is possible to emphasize increasing the size of tail-wagging motions, mouth-opening motions (to suppress excitement), and dance-type motions. For example, in response to an external situation where a room is bright, it is possible to emphasize increasing the size of paw motions or motions that are performed in response to recognition of something. For example, in response to an external situation where a favorite object is within the field of view, it is possible to emphasize increasing the size of dance-type motions.

[0188] FIG. 24 is a diagram illustrating an example of an internal state and a manner in which motion is emphasized or suppressed in conjunction with the internal state.

[0189] For example, in conjunction with the (state of) desire for food as an internal state, it is possible to suppress the paw motion to a lower level, emphasize the eating motion to a higher level, and emphasize the "is it ready yet?" motion to beg for food to a higher level. For example, in conjunction with the (state of) emotion of having failed to grasp as an internal state, it is possible to emphasize the sad cry motion to a higher level. For example, in conjunction with the internal state of a personality being shy, it is possible to suppress the pee motion to a lower level. For example, in conjunction with the internal state of a sad or depressed emotion, it is possible to emphasize the sad cry motion to a higher level. For example, in conjunction with the internal state of a desire to be full or to be full after eating food, it is possible to suppress the paw motion to a lower level and emphasize the eating motion to a higher level. For example, in conjunction with the internal state of a feeling of having successfully grasped something, it is possible to emphasize the throwing away what was grasped or the happy motion to a higher level. For example, in conjunction with a wild personality internal state, it is possible to increase the intensity of sneezing, burping, and yawning motions, increase the intensity of the pee motion when transitioning to a sitting position, and increase the intensity of the pee motion. For example, in conjunction with an angry emotion internal state, it is possible to increase the intensity of growling motions and barking motions. For example, in conjunction with a happy emotion internal state, it is possible to increase the intensity of happy motions and increase the intensity of dance-type motions. For example, in conjunction with a hot internal state, it is possible to reduce the head shaking motion when barking and reduce the paw motion. For example, in conjunction with a low battery internal state, it is possible to reduce seasonal dance motions according to the season, reduce nodding motions, and increase motions expressing fatigue. For example, in conjunction with a broken internal state, it is possible to reduce all motions.For example, in conjunction with the internal state of being elderly, it is possible to suppress the motions by making them smaller overall, or to emphasize by making larger the "dokkoisho" motion when transitioning to a sitting position. For example, in conjunction with the internal state of having just had a full battery, it is possible to emphasize by making larger the head shaking motion when barking, by making larger the paw motion, or by making larger the motion of throwing a dice or bone provided as a toy for the moving body 10. For example, in conjunction with the internal state of being young, it is possible to emphasize by making larger the motion of throwing a toy dice or bone, by making larger the motion of the swing when throwing the dice or bone, by making larger the dance-type motion, or by making larger the motion of standing up.

[0190] FIG. 25 is a diagram illustrating an example of personality as an internal state and adjustment of motion elements in emphasizing or suppressing motions performed in conjunction with the personality.

[0191] As described with reference to FIG. 4, the motion elements to be adjusted include the amplitude, speed, preparatory movement, and swing back of the motion.

[0192] For example, if the personality of the moving body 10 as an internal state is cute, then in conjunction with this cute personality, the moving body 10 can be made to perform a modified motion in which the amplitude, speed, and swing back of the motion are the same as the default motion, and the preparatory movement is larger than the default motion.

[0193] The motions (target motions) that the moving body 10 performs modified motions in conjunction with the external situation and / or the internal state may be all or some of the motions that the moving body 10 is capable of. The part of the motions that are the target motions may be set based on the internal state of the moving body 10, such as personality, for example.

[0194] For example, a dance-type motion can be adopted as a target motion (default motion) for causing the cute-personality moving body 10 to perform a modified motion. In a modified motion of a dance-type motion, the amplitude, speed, and swing are the same as in the default motion, and the preparatory movement is made larger than in the default motion, resulting in a dance that is more emphasized than in the default motion.

[0195] For example, if the personality of the moving body 10 as an internal state is that of a spoiled person, then in accordance with this spoiled personality, the moving body 10 can be made to perform a modified motion in which the amplitude of the motion is made larger than that of the default motion, the speed is made smaller than that of the default motion, the preparatory motion is the same as that of the default motion, and the swing-back is made larger than that of the default motion.

[0196] As a target motion for causing a moving body 10 with a spoiled personality to perform a modified motion, for example, a motion called a boredom act (a motion performed in response to a motion event of being bored) can be adopted.

[0197] For example, if the personality of the moving body 10 as an internal state is shy, then in response to this shy personality, the moving body 10 can be made to perform a modified motion in which the amplitude and speed of the motion are smaller than those of the default motion, and the preparatory movement and swing-back are the same as those of the default motion.

[0198] As the target motion for causing the shy moving body 10 to perform a modified motion, for example, all motions can be adopted.

[0199] For example, if the character as an internal state of the moving body 10 is wild, then in conjunction with this wild character, the moving body 10 can be made to perform a modified motion in which the amplitude and speed of the motion are made larger than in the default motion, and the preparatory movement and swing back are made larger than in the default motion.

[0200] As the target motion for causing the moving body 10 with a wild personality to perform a modified motion, for example, a sneezing motion and a burping motion can be adopted.

[0201] As described above, the operating body 10 performs modified motions in conjunction with the character as an internal state, allowing the user to understand the individuality and personality of the operating body 10. For example, in a sneezing motion, the user can understand that the character is wild by seeing the mouth open widely. Also, in a joy motion, the user can understand that the character is clingy by seeing the tail wagging widely. Therefore, the entertainment value of the operating body 10 can be improved by allowing the user to sense the difference in individuality and personality between the operating body 10 that the user owns and the operating bodies owned by other users, and further allowing the user to feel an attachment to the operating body 10 that the user owns.

[0202] <Virtual characters using this technology>

[0203] FIG. 26 is a diagram illustrating an example configuration of an embodiment of an information processing system that provides a virtual character as a moving object to which the present technology is applied.

[0204] In FIG. 26, an information processing system 120 is configured by connecting a server 121 and a terminal 122 via a network 123 such as the Internet.

[0205] The server 121 generates a 2D (dimensional) image or 3D image (data) of the virtual character 110 , which is a virtual character, and transmits it to the user's terminal 122 via the network 123 .

[0206] The terminal 122 displays the virtual character 110 from the server 121 .

[0207] The virtual character 110 autonomously performs various motions based on the external situation and / or internal state, etc., similar to the moving body 10. Furthermore, the virtual character 110, similar to the moving body 10, performs modified motions that emphasize or suppress default motions in conjunction with the external situation and / or internal state of the virtual character 110.

[0208] In addition, in a moving body 10 that actually exists, various motions are performed by the actual movement of the joints of the moving body 10, but in a virtual character 110, various motions are performed by drawing an image of the virtual character 110.

[0209] A virtual character that is a reproduction of the operating body 10 that actually exists in the virtual world can be used as the virtual character 110. In this case, the server 121 acquires internal state information of the operating body 10 by communicating with the operating body 10 via the network 123, and generates the virtual character 110 that performs the same motion as the operating body 10 using the internal state information.

[0210] When a virtual character that reproduces the moving body 10 in the virtual world is adopted as the virtual character 110, the user can communicate with the virtual character 110 in the virtual world displayed on the terminal 122 as if he or she were communicating with the moving body 10, even if the user does not take the moving body 10 with him or her when he or she is away from home.

[0211] The virtual character 110 may be an independent, virtual character that exists independently of the operating body 10 that actually exists.

[0212] <Toy robot applying this technology>

[0213] FIG. 27 is a perspective view showing an example of the external configuration of an embodiment of a toy robot as a moving body to which the present technology is applied.

[0214] In FIG. 27, a moving body 210 is a robot that exists in reality, similar to the moving body 10 in FIG. 1, and autonomously performs various motions.

[0215] The operating body 210 is a toy robot, and has a substantially cylindrical shape, with a head 211 at the top and rollers 212 at the bottom.

[0216] The head 211 is hemispherical and can rotate by a predetermined angle around each of the three axes (x, y, and z). Furthermore, the head 211 has a display unit that displays images as the toy robot's eyes. By rotating the head 211, it is possible to express changes in the angle of the face, and by combining this rotation of the head 211 with the display of the eyes on the head 211, the moving body 210 as a toy robot can realize a wide range of facial expressions.

[0217] The rollers 212 are provided on the left and right, like left and right feet. When the left and right rollers 212 rotate in the same direction, the moving body 210 can move forward and backward. When the left and right rollers 212 rotate in different directions, the moving body 210 can rotate counterclockwise or clockwise and change direction.

[0218] The electrical configuration of the moving body 210 is the same as that of the moving body 10 shown in Fig. 2. Therefore, like the moving body 10, the moving body 210 can autonomously perform various motions based on the external situation and / or the internal state, and further can perform modified motions that emphasize or suppress default motions in conjunction with the external situation and / or the internal state.

[0219] The moving body 210 can move using rollers 212 and can perform motions involving relatively quick movement. Furthermore, the moving body 210 can output sounds as motions, such as the cry output described in Fig. 2 and sound effects using onomatopoeia that express the movement, as well as utterances in natural languages.

[0220] Therefore, the moving body 210 can express its intentions, etc., to the user in a way that is easier to understand (and understand) by, for example, performing a motion that combines movement by the rollers 212 and outputting sounds such as utterances in natural language. For example, by moving around excitedly and uttering the word "I'm happy," as well as outputting sound effects that express the movement, it is possible to express happiness in an easy-to-understand manner that is easy for the user to empathize with.

[0221] In the moving body 210, emphasis or suppression of the default motion linked to the external situation and / or internal state can be performed on the rotation of the head 211, the display and movement of the eyes, and the output of sound in the head 211. By inputting time-series data that controls the rotation of the head 211, the display and movement of the eyes, and the time-series data of the sounds and sound effects to be output in the sound output as default data into a motion emphasizer, the rotation of the head 211, the display and movement of the eyes, and the output of sound can be performed in accordance with modified data, thereby making it possible to perform motions (modified motions) with rich expressions.

[0222] FIG. 28 is a diagram illustrating an example of modified motion (emphasized motion) in which the default motion of moving the moving body 210 by the rollers 212 is emphasized.

[0223] FIG. 28A shows an example of a locus of movement on the xy plane as the motion of the moving body 210 that can be moved by the rollers 212 .

[0224] In A of Fig. 28, the movement as default motion according to the default data d(t) is a movement that describes a (nearly) linear locus along the x-axis, while the movement as modified motion according to the modified data m(t) generated by inputting the default data d(t) into the motion enhancer is a movement that describes a slalom-like locus that meanders on the xy plane.

[0225] FIG. 28B shows an example of movement in the x-axis direction as a motion of the moving body 210 that can be moved by the rollers 212 .

[0226] In Figure 28B, the default motion according to the default data d(t) is a motion that stops (almost) motionless in the x-axis direction, while the modified motion according to the modified data m(t) generated by inputting the default data d(t) into the motion enhancer is a motion that alternates between one direction and the opposite direction in the x-axis direction.

[0227] <Description of a computer to which this technology is applied>

[0228] Next, the above-described series of processes can be performed by hardware or software. When the series of processes is performed by software, the programs that make up the software are installed on a general-purpose computer or the like.

[0229] FIG. 29 is a block diagram showing an example of the configuration of an embodiment of a computer in which a program for executing the above-described series of processes is installed.

[0230] The program can be recorded in advance on the hard disk 905 or ROM 903 as a recording medium built into the computer.

[0231] Alternatively, the program can be stored (recorded) on a removable recording medium 911 driven by the drive 909. Such a removable recording medium 911 can be provided as a so-called package software. Here, examples of the removable recording medium 911 include a flexible disk, a CD-ROM (Compact Disc Read Only Memory), an MO (Magneto Optical) disk, a DVD (Digital Versatile Disc), a magnetic disk, and a semiconductor memory.

[0232] The program can be installed into the computer from the removable recording medium 911 as described above, or can be downloaded to the computer via a communication network or a broadcasting network and installed on the built-in hard disk 905. That is, the program can be transferred to the computer wirelessly from a download site via an artificial satellite for digital satellite broadcasting, or transferred to the computer via a wired network such as a LAN (Local Area Network) or the Internet.

[0233] The computer includes a CPU (Central Processing Unit) 902 , to which an input / output interface 910 is connected via a bus 901 .

[0234] When a user inputs a command via an input / output interface 910 by operating an input unit 907, the CPU 902 executes a program stored in a read-only memory (ROM) 903 in accordance with the command. Alternatively, the CPU 902 loads a program stored on a hard disk 905 into a random access memory (RAM) 904 and executes the program.

[0235] As a result, the CPU 902 performs processing according to the flowchart described above or processing performed by the configuration of the block diagram described above. Then, the CPU 902 outputs the processing results from the output unit 906 via the input / output interface 910, or transmits them from the communication unit 908, or further records them on the hard disk 905, as necessary.

[0236] The input unit 907 is made up of a keyboard, a mouse, a microphone, etc. The output unit 906 is made up of an LCD (Liquid Crystal Display), a speaker, etc.

[0237] In this specification, the processing performed by a computer according to a program does not necessarily have to be performed in chronological order according to the order described in the flowchart. In other words, the processing performed by a computer according to a program also includes processing that is executed in parallel or individually (for example, parallel processing or object-based processing).

[0238] The program may be processed by a single computer (processor), or may be distributed among multiple computers. Furthermore, the program may be transferred to and executed on a remote computer.

[0239] Furthermore, in this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all of the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0240] It should be noted that the embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible within the scope of the present technology.

[0241] For example, the present technology can be configured as a cloud computing system in which a single function is shared and processed collaboratively by a plurality of devices via a network.

[0242] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by a plurality of devices.

[0243] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0244] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0245] The present technology can have the following configurations.

[0246] <1> An information processing device comprising a control unit that controls a moving object to perform a motion that emphasizes or suppresses the motion in accordance with predetermined motion data in conjunction with an external situation and / or an internal state of the moving object performing the motion in accordance with the predetermined motion data. <2> The information processing device described in <1>, wherein the control unit controls the moving object in accordance with modified data, which is motion data generated using the predetermined motion data and causes the moving object to perform a motion that emphasizes or suppresses the motion in accordance with the predetermined motion data. <3> The information processing device described in <2>, wherein the control unit generates the modified data using the predetermined motion data. <4> The information processing device described in <2> or <3>, wherein an emphasis component for emphasizing the motion in accordance with the predetermined motion data is generated using the predetermined motion data, and the modified data for causing the emphasized motion that emphasizes the motion in accordance with the predetermined motion data is generated using the emphasis component. <5> The information processing device described in <4>, wherein the emphasis component is generated by applying a LoG (Laplacian of Gaussian) filter to the predetermined motion data. <6> The information processing device according to <4> or <5>, wherein the modified data is generated using an emphasis coefficient that adjusts the degree of emphasis by the emphasis component. <7> The information processing device according to any of <4> to <6>, wherein the modified data is generated by adding the predetermined motion data and the emphasis component. <8> The information processing device according to <7>, wherein the modified data is generated using an addition coefficient that adjusts the interval to which the emphasis component is added. <9> The information processing device according to <6>, wherein the emphasis coefficient is set so that the modified data falls within the range of motion of the moving object. <10> The information processing device according to any of <2> to <9>, wherein the modified data is converted using a limiting coefficient that adjusts the modified data so that it falls within the range of motion of the moving object.<11> The information processing device according to <10>, wherein the limiting coefficient converts the modified data nonlinearly so as to make an adjustment that limits the modified data having a larger magnitude more than the modified data having a smaller magnitude. <12> The information processing device according to any of <2> to <11>, wherein modified data for the repeat default data is generated using repeat default data obtained by repeating a repeatable repeat portion of the predetermined motion data, modified data for the motion data of the non-repeat portion is generated using motion data of a non-repeat portion connected to the repeat portion, and modified data for the motion data of the repeat portion and the non-repeat portion is generated using data obtained by interpolating so as to smoothly connect the modified data for the repeat default data and the modified data for the motion data of the non-repeat portion. <13> The information processing device according to any one of <2> to <12>, wherein the modified data for causing a suppressed motion that suppresses a motion in accordance with the predetermined motion data is generated by weighted addition of the predetermined motion data and a second-order derivative of the predetermined motion data. <14> The information processing device according to <13>, wherein the second-order derivative of the predetermined motion data is generated by applying a LoG (Laplacian of Gaussian) filter to the predetermined motion data. <15> The information processing device according to any one of <2> to <12>, wherein the modified data for causing an emphasized motion that emphasizes a motion in accordance with the predetermined motion data is generated by weighted addition of the predetermined motion data and an odd power of the predetermined motion data. <16> The information processing device according to any one of <1> to <15>, wherein the control unit controls the moving object to perform a motion that emphasizes or suppresses the motion in accordance with the predetermined motion data in conjunction with handclaps or beats per minute (bpm) of music as the external situation.<17> The information processing device according to any one of <1> to <16>, wherein the control unit controls the moving body to perform a motion that emphasizes or suppresses the motion in accordance with the predetermined motion data in conjunction with personality or emotion as the internal state. <18> The information processing device according to any one of <1> to <17>, wherein the moving body is a robot that exists in reality or a virtual character. <19> An information processing method including controlling the moving body to perform a motion that emphasizes or suppresses the motion in accordance with the predetermined motion data in conjunction with an external situation and / or an internal state of the moving body that performs the motion in accordance with the predetermined motion data. <20> A program for causing a computer to function as a control unit that controls the moving body to perform a motion that emphasizes or suppresses the motion in accordance with the predetermined motion data in conjunction with an external situation and / or an internal state of the moving body that performs the motion in accordance with the predetermined motion data.

[0247] 10 Operating body, 21 Sensor device, 22 Information processing device, 23 Motion execution device, 31 Pick-up detection unit, 32 Control unit, 41 Drive unit, 42 Sound output unit, 43 Display unit, 110 Virtual character, 120 Information processing system, 121 Server, 122 Terminal, 123 Network, 210 Operating body, 211 Head, 212 Roller, 901 Bus, 902 CPU, 903 ROM, 904 RAM, 905 Hard disk, 906 Output unit, 907 Input unit, 908 Communication unit, 909 Drive, 910 Input / output interface, 911 Removable recording medium

Claims

1. An information processing device having a control unit that controls a moving body to perform a motion that emphasizes or suppresses the motion in accordance with predetermined motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion in accordance with the predetermined motion data.

2. The information processing device according to claim 1, wherein the control unit controls the moving body in accordance with modified data, which is motion data generated using the specified motion data and which causes the moving body to perform a motion that emphasizes or suppresses a motion in accordance with the specified motion data.

3. The information processing device according to claim 2, wherein the control unit generates the modified data using the predetermined motion data.

4. An information processing device as described in claim 2, wherein an emphasis component for emphasizing motion according to the specified motion data is generated using the specified motion data, and the modified data for performing an emphasis motion that emphasizes motion according to the specified motion data is generated using the emphasis component.

5. The information processing device according to claim 4, wherein the emphasized components are generated by applying a LoG (Laplacian of Gaussian) filter to the predetermined motion data.

6. The information processing device according to claim 4, wherein the modified data is generated using an emphasis coefficient that adjusts the degree of emphasis by the emphasis component.

7. The information processing device according to claim 4, wherein the modified data is generated by adding the predetermined motion data and the emphasis component.

8. The information processing device according to claim 7, wherein the modified data is generated using an addition coefficient that adjusts the section to which the emphasis component is added.

9. The information processing device according to claim 6, wherein the emphasis coefficient is set so that the modified data falls within the range of motion of the moving object.

10. The information processing device according to claim 2, wherein the modified data is converted using a limiting coefficient that adjusts the modified data so that it fits within the range of motion of the moving object.

11. The information processing device according to claim 10, wherein the limiting coefficient converts the modified data nonlinearly so as to adjust the modified data such that the modified data having a large magnitude is more limited than the modified data having a small magnitude.

12. An information processing device as described in claim 2, wherein modified data for the repeat default data is generated using repeat default data that repeats a repeatable repeat portion of the specified motion data; modified data for the motion data for the non-repeat portion is generated using motion data for the non-repeat portion that connects to the repeat portion; and modified data for the motion data for the repeat portion and the non-repeat portion is generated using data obtained by interpolating so as to smoothly connect the modified data for the repeat default data and the modified data for the motion data for the non-repeat portion.

13. The information processing device according to claim 2, wherein the modified data for performing a suppressed motion that suppresses a motion according to the predetermined motion data is generated by weighted addition of the predetermined motion data and a second derivative of the predetermined motion data.

14. The information processing device according to claim 13, wherein the second derivative of the predetermined motion data is generated by applying a LoG (Laplacian of Gaussian) filter to the predetermined motion data.

15. An information processing device according to claim 2, wherein the modified data for performing an emphasis motion that emphasizes a motion according to the predetermined motion data is generated by weighted addition of the predetermined motion data and an odd power of the predetermined motion data.

16. The information processing device according to claim 1, wherein the control unit controls the moving body to perform a motion that emphasizes or suppresses a motion according to the specified motion data in conjunction with the external situation such as clapping or the bpm (beats per minute) of music.

17. The information processing device according to claim 1, wherein the control unit controls the moving body so as to perform a motion that emphasizes or suppresses a motion according to the predetermined motion data in conjunction with the personality or emotion as the internal state.

18. The information processing device according to claim 1, wherein the moving body is a robot that exists in reality or a virtual character.

19. An information processing method including controlling a moving body to perform a motion that emphasizes or suppresses the motion in accordance with predetermined motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion in accordance with the predetermined motion data.

20. A program for causing a computer to function as a control unit that controls a moving body to perform a motion that emphasizes or suppresses the motion in accordance with specified motion data in conjunction with the external situation and / or internal state of the moving body that performs the motion in accordance with the specified motion data.

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