Control device, control system, control method, program

Abstract

To provide a technique capable of allowing a user to give instructions to a predetermined device with minimum motion.SOLUTION: A control device acquires a signal indicating motion of muscles of a predetermined part of a body of a user wearing a powered suit. The control device extracts a signal giving an instruction for an instruction object on the basis of the signal indicating the motion of the muscles of the predetermined part of the body of the user. The control device transmits the signal of giving the instruction for the instruction object, to the instruction object.SELECTED DRAWING: Figure 1

Description

Technical Field

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

Background Art

[0002] Technologies for power suits that assist a user's body movements have been studied. In this technology, a technology in which a user wearing a power suit gives a predetermined instruction to a predetermined external device using a device provided in the power suit has also been studied.

[0003] Patent Document 1 discloses a technology of an operator terminal that transmits an operation instruction to a robot used in work. In this technology, an operation instruction is given to the robot based on a signal from a sensor that detects the myoelectric potential of the operator.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] When giving an instruction to a predetermined device as described above, there is a need for a technology that allows a user to give an instruction with as few movements as possible.

[0006] Therefore, an object of this invention is to provide a control device, a control system, a control method, and a program that solve the above problems.

Means for Solving the Problems

[0007] According to a first aspect of the invention, the control device includes an acquisition means for acquiring signals indicating muscle movements of body parts of a user wearing a powered suit, an extraction means for extracting signals indicating that the muscle movements indicate instructions for a target based on the signals indicating muscle movements of the body parts of the user, and a transmission means for transmitting signals indicating instructions for the target to the target.

[0008] According to a second aspect of the invention, the control method includes a control device that acquires signals indicating muscle movements of a body part of a user wearing a powered suit, extracts a signal indicating that the muscle movements indicate an instruction to a target based on the signals indicating muscle movements of the body part of the user, and transmits the signal indicating an instruction to the target to the target.

[0009] According to a first aspect of the invention, the program causes the computer of the control device to function as an acquisition means for acquiring signals indicating muscle movements of body parts of a user wearing a powered suit, an extraction means for extracting signals indicating that the muscle movements indicate instructions for a target based on the signals indicating muscle movements of the user's body parts, and a transmission means for transmitting signals indicating instructions for the target to the target. [Effects of the Invention]

[0010] According to the present invention, when giving instructions to a predetermined device, the user can give instructions with as few movements as possible. [Brief explanation of the drawing]

[0011] [Figure 1] This is the first figure showing the schematic configuration of the control system according to this embodiment. [Figure 2] This is a functional block diagram of the powered suit according to this embodiment. [Figure 3] This figure shows a schematic configuration of the arm area of ​​the powered suit according to this embodiment. [Figure 4] This figure shows the schematic configuration of the upper body front of the powered suit according to this embodiment. [Figure 5] This is a functional block diagram of the unmanned vehicle according to this embodiment. [Figure 6] This figure shows an overview of the processing of the control device according to this embodiment. [Figure 7] This is the first figure showing the processing flow of the control system according to this embodiment. [Figure 8] This is the second figure showing the processing flow of the control system according to this embodiment. [Figure 9] This is the second figure, which shows a schematic configuration of the control system according to this embodiment. [Figure 10] This is a third figure showing the schematic configuration of the control system according to this embodiment. [Figure 11] This diagram shows the minimum configuration of the control device. [Figure 12] This figure shows the processing flow of a control device with a minimum configuration. [Figure 13] This block diagram schematically shows an example of a hardware configuration for a computing device that can implement a control unit. [Modes for carrying out the invention]

[0012] A control device according to one embodiment of the present invention will be described below with reference to the drawings. Figure 1 is a schematic diagram of a control system including a powered suit equipped with a control device according to this embodiment. As shown in Figure 1, the control system 100 is configured by wireless communication between a powered suit 10 equipped with a control device 20 and an unmanned ground vehicle 30.

[0013] The power suit 10 is configured to be worn by a user on the upper body and the lower body. As an example, the power suit 10 has a control device 20 and various sensors attached to each frame connected via a plurality of actuators 230 located near joints along the arms, legs, waist, back, etc. The plurality of actuators 230 are provided near the hip, knee, ankle, shoulder, upper arm, and wrist. The plurality of sensors 210 are provided at the hip joint, knee joint, ankle joint, shoulder joint, upper arm joint, wrist joint, upper arm, thigh, chest, etc. More specifically, the power suit 10 has sensors 210 attached to belts 11 to 16 provided at the waist, chest, upper arm, forearm, thigh, lower knee, etc. of the frame. Also, drive devices 270 are attached to belts 14 and 16 provided at the forearm, lower knee, etc. The control device 20 is driven by the power obtained from the battery 40. The control device 20 is communicatively connected to the unmanned vehicle 30 via wireless communication.

[0014] Figure 2 is a functional block diagram of the power suit. The control device 20 exhibits the functions of a power supply unit 21, a storage unit 22, a communication unit 23, and an integrated control unit 24. The integrated control unit 24 exhibits the functions of an extraction unit 241, a motion estimation unit 242, a fatigue degree estimation unit 243, a signal recognition unit 244, and a signal generation unit 245. Also, the control device 20 exhibits the functions of an information acquisition unit 25, an actuator control unit 26, and a haptics control unit 27. [[ID=~]]

[0015] The power supply unit 21 supplies the power obtained from the battery 40 to each hardware function within the control device 20. The storage unit 22 stores the information used by the control device 20 for each process. The communication unit 23 is communicatively connected to an external device such as the unmanned vehicle 30. The integrated control unit 24 manages each process of the extraction unit 241, the motion estimation unit 242, the fatigue degree estimation unit 243, the signal recognition unit 244, and the signal generation unit 245.

[0016] The extraction unit 241 extracts signals indicating instructions for a target based on signals indicating muscle movements in predetermined parts of the user's body wearing the powered suit 10. In this extraction, the extraction unit 241 separates the operation signals of the user's normal movements from the instruction signals indicating instructions for a target from the signals obtained from the information acquisition unit 25. The motion estimation unit 242 estimates the user's actions based on the motion signals of normal user operation separated by the extraction unit 241 and outputs an estimated motion signal. The fatigue level estimation unit 243 estimates the user's fatigue level based on the operation signals of the user's normal operation separated by the extraction unit 241, the user's vital signals, and the operation estimation results of the operation estimation unit 242, and outputs a fatigue level estimation signal. The signal generation unit 245 generates a transmission signal to be sent to the unmanned vehicle 30, which is the target of the instruction. The signal recognition unit 244 recognizes the instruction response received from the unmanned vehicle 30, which is the target of the instruction.

[0017] The control device 20 also performs the functions of the information acquisition unit 25, the actuator control unit 26, and the haptics control unit 27. The information acquisition unit 25 acquires sensing information from each sensor 210. The actuator control unit 26 controls each actuator 230. The haptics control unit 27 controls a device that utilizes haptic technology, such as a solenoid, which is a drive device 270, based on the recognition result of the signal recognition unit 244 that recognizes the response signal.

[0018] The control device 20 communicates with each sensor 210. The sensors 210 include a hip joint sensor 211, a knee joint sensor 212, ankle joint sensor 213, a shoulder joint sensor 214, an elbow joint sensor 215, a wrist joint sensor 216, an upper arm sensor 217, a thigh sensor 218, a chest sensor 219, and so on. Each sensor 210 is attached near the hip, knee, ankle, shoulder, elbow, wrist, upper arm, thigh, chest, etc. For convenience, in Figure 2, the inertial sensor 221, angular velocity sensor 222, and force sensor 223 are shown only under the hip joint sensor 211, but each sensor 210 may have one or more functions of an inertial sensor 221, angular velocity sensor 222, force sensor 223, electromyography sensor 224, or vital sign sensor 225.

[0019] The information acquisition unit 25 acquires the information sensed by each of these sensors 210. The force sensor 223 is attached to the side of the belts 11-16 that comes into contact with the user's body and senses a physical quantity corresponding to the force applied by the user to a predetermined part of the body to which the sensor 210 is attached. The force sensor 223 can be a piezoelectric sensor or a film-type sensor that measures pressure from changes in the resistance value of the sensor part. It is also possible to sense the force applied by the user to a predetermined part of the body to which the force sensor 223 is attached by measuring the length of the belt to which the force sensor 223 is attached, or the displacement of the belt's shape. The force sensor 223 outputs the sensed information converted into an electrical signal such as a voltage value to the information acquisition unit 25. The electromyography sensor 224 outputs sensed information to the information acquisition unit 25 that shows an electrical signal corresponding to muscle movement obtained from a terminal in contact with the user's skin.

[0020] The control device 20 communicates with each actuator 230. The actuators 230 include a hip actuator 231, a knee actuator 232, ankle actuator 233, a shoulder actuator 234, an elbow actuator 235, a wrist actuator 236, etc., which are attached to joint positions such as the hip, knee, ankle, shoulder, elbow, and wrist, respectively. Each actuator 230 has a built-in motor, which is driven by the actuator control unit 26 to assist the force applied by the user.

[0021] The control device 20 communicates with one or more drive devices 270. One embodiment of the drive device 270 is a solenoid, which may be, for example, an arm solenoid 271 attached to the arm, a shin solenoid 272 attached to the shin, etc. The arm solenoid 271 and the shin solenoid 272 convert electrical energy into mechanical linear motion in a piston part or the like. When the haptics control unit 27 controls the arm solenoid 271 and the shin solenoid 272, the piston part of each solenoid operates, and the tip of the piston comes into contact with the user's skin, either through the user's clothing or directly. Based on the response signal recognized by the signal recognition unit 244, the haptics control unit 27 controls the arm solenoid 271 and the shin solenoid 272 and conveys information to the user corresponding to the response signal. The user recognizes the information based on the response signal based on the number of times the piston indirectly or directly contacts the skin per unit time, the duration of indirect or direct contact with the skin, etc. The drive device 270 may be a device that applies haptic technology other than a solenoid. The drive device 270 is not limited to a device that applies haptic technology; it may be any device that can notify the user of information corresponding to the response signal of the unmanned vehicle 30 without being recognized as much as possible by other people or other external parties.

[0022] In the example above, the powered suit is shown with a cargo platform on its back, but this is not a requirement. Powered suits for applications that do not require carrying cargo on the back do not need a cargo platform. Also, in the example above, actuators are attached to each joint, but this is not a requirement. Whether or not to attach actuators to each joint is a matter of personal choice. Furthermore, in the example above, motors are used to assist the force of the actuators, but this is not a requirement. Artificial muscles, springs, etc., may be used as actuators.

[0023] Figure 3 shows a schematic diagram of the arm area of ​​the powered suit. Figure 3 illustrates the schematic configuration of the powered suit 10 for the user's arm. The user's upper arm is wrapped around a belt 13 equipped with an upper arm sensor 217 over the user's clothing. A force sensor 223 included in the upper arm sensor 217 is located between the user's clothing and the belt 13. The force sensor 223 senses the movement of the user's upper arm muscles through the clothing.

[0024] Furthermore, the forearm is wrapped around the user's clothing by a belt 14 equipped with an arm solenoid assembly 271. The solenoid assembly of the arm solenoid 271 is located between the user's clothing and the belt 14. This solenoid assembly consists of, for example, nine solenoids arranged in a 3x3 grid, and can convey arbitrary information to the user through combinations of the actions of each solenoid.

[0025] Figure 4 shows a schematic diagram of the upper body front of the powered suit. Figure 4 illustrates the configuration of the user's chest belt 12. The user wears the powered suit over their clothes. Figure 4 is a front view of the user. The user wears the powered suit 10 on their back, with the left and right belts 12, equipped with chest sensors 219 including force sensors 223 and vital sensors 225, draped over their shoulders. The force sensor 223 is located between the user's clothing and the chest belt 12. The chest force sensor 223 senses the movement of the user's chest muscles through the clothing.

[0026] Figure 5 is a functional block diagram of an unmanned vehicle. The unmanned vehicle 30 performs the functions of a power supply unit 31, a memory unit 32, a communication unit 33, an integrated control unit 34, an information acquisition unit 35, and a vehicle control unit 36. The integrated control unit 34 also performs the functions of an environment recognition unit 341, a self-position estimation unit 342, a block sign recognition unit 343, a fatigue level recognition unit 344, a fatigue level prediction unit 345, a route planning unit 346, and a signal generation unit 347.

[0027] The power supply unit 31 supplies power obtained from the battery to each hardware function within the unmanned vehicle 30. The memory unit 32 stores information used by the unmanned vehicle 30 for each process. The communication unit 33 communicates with the control device 20 of the powered suit 10. The integrated control unit 34 manages the processes of the environment recognition unit 341, the self-position estimation unit 342, the block sign recognition unit 343, the fatigue level recognition unit 344, the fatigue level prediction unit 345, the path planning unit 346, and the signal generation unit 347.

[0028] The unmanned vehicle 30 may be equipped with sensing devices 300 such as a LiDAR 314, a millimeter-wave sensor 315, a visible light camera 316, an inertial sensor 317, a GPS 318, an environmental sensor 319, and a weather information acquisition device 320. The information acquisition unit 35 outputs the information acquired from these sensing devices 300 to the integrated control unit 34. The vehicle control unit 36 ​​controls the drive unit 37 and other components that drive the wheels of the unmanned vehicle 30.

[0029] The environmental recognition unit 341 recognizes information such as weather and the surrounding environment based on the sensing information obtained from the sensing device 300. The self-position estimation unit 342 calculates the position of the unmanned vehicle 30 based on information obtained from a GNSS sensor such as a GPS 318. The block sign recognition unit 343 recognizes block signs issued by the user based on instruction signals and the like acquired from the control device 20 of the powered suit 10. The fatigue level recognition unit 344 recognizes the user's fatigue level calculated by the control device 20 based on operation signals, vital signals, fatigue level estimation signals, etc. The fatigue level prediction unit 345 predicts the user's future fatigue level based on the fatigue level and the route plan indicating the user's future travel route shown by the route planning unit 346. The route planning unit 346 generates information indicating the route the user takes to reach a predetermined destination. The signal generation unit 347 generates response signals based on instruction signals and other signals such as fatigue level prediction signals.

[0030] In such a control system 100, the user wearing the powered suit 10 consciously exerts force on the muscles of their left and right upper arms, thighs, and chest in any pattern, and emits block signs corresponding to the instructions given to the unmanned vehicle 30 through muscle movement. At this time, the user does not need to perform gesture movements such as bending joints. For example, the information acquisition unit 25 acquires sensing information captured by the muscle movement from the force sensors 223 included in the left and right upper arm sensors 217 and the force sensor 223 of the thigh sensor 218 attached to the thigh, and outputs it to the extraction unit 241. The extraction unit 241 captures block signs based on the sensing information obtained from each sensor. The motion estimation unit 242 may estimate the user's motion based on the sensing information. The fatigue level estimation unit 243 may estimate the user's fatigue level based on the sensing information. The integrated control unit 24 transmits the block sign information and instruction signals including the estimated user motion and fatigue level to the unmanned vehicle 30 via the communication unit 23.

[0031] The unmanned vehicle 30 is an example of an object to be instructed. The unmanned vehicle 30 receives instruction signals, motion signals, vital signals, motion estimation signals, fatigue estimation signals, etc., transmitted from the powered suit 10. The unmanned vehicle 30 detects block signs based on the instruction signals and detects motion, fatigue level, etc., based on motion signals, vital signals, motion estimation signals, fatigue level, etc. The unmanned vehicle 30 generates response information based on block signs, user motion, fatigue level, etc. The response information may include, for example, instructions to the user or recommended routes for the user to travel. The unmanned vehicle 30 transmits a response signal containing the response information to the control device 20. The control device 20 drives the drive device 270 using haptic technology based on the response signal. This allows the user to recognize responses such as instructions from the unmanned vehicle 30 in accordance with the response signal.

[0032] In this way, a user wearing the powered suit 10 can communicate with the unmanned vehicle 30 at any time through the powered suit 10 using block signals consisting only of muscle movements, and as a result, can carry out highly confidential tasks. A block signal is an instruction represented by a predetermined movement or sequence of predetermined movements of the muscles of one or more predetermined parts of the body.

[0033] Figure 6 shows an overview of the control device's processing. Figure 6 shows an overview of the roles of the information acquisition unit 25, extraction unit 241, motion estimation unit 242, fatigue level estimation unit 243, and signal generation unit 245 in the control device 20. The information acquisition unit 25 acquires sensing information. The extraction unit 241 performs signal separation, block sign determination, and instruction signal generation. The motion estimation unit 242 estimates the user's actions. The fatigue level estimation unit 243 estimates the user's fatigue level. The signal generation unit 245 generates transmission information from the instruction signal, operation signal, operation estimation signal, and fatigue level estimation signal.

[0034] Figure 7 is the first diagram showing the processing flow of the control system. Next, we will explain the processing flow of the control unit. A user wearing the powered suit 10 moves the muscles of a predetermined part of their body. At this time, the user does not make gestures such as swinging their arms. A force sensor 223 attached near the body part outputs sensing information to the control device 20. The information acquisition unit 25 outputs the sensing information to the extraction unit 241. The extraction unit 241 acquires the sensing information (step S101). The extraction unit 241 analyzes the electrical signals corresponding to the muscle movements indicated by the sensing information, extracts the muscle movements that indicate a block sign, and generates an instruction signal (step S102). For example, if the sensing information is a signal indicating that force has been applied to a predetermined number of times per unit time, the extraction unit 241 detects that it is a signal indicating a block sign and extracts that signal. The extraction unit 241 may also detect that the signal indicating muscle movement indicated by the sensing information is a signal indicating that force has been applied continuously for a predetermined time. The extraction unit 241 may also detect that the signal included in the sensing information is a signal indicating a block sign through other processing. For example, the extraction unit 241 may input information about the muscle signal indicated by the sensing information into a neural network using an extraction model generated by machine learning, and based on the output information obtained as a result, detect whether the signal indicates a block sign. This makes it possible to determine whether the sensing information contains signals that constitute a block sign or not.

[0035] The extraction unit 241 determines that a first action has occurred if it detects that a predetermined number of forces have been applied per unit time, based on the electrical signal from the force sensor 223 included in the chest sensor 219. The first action is an action in which the chest muscles are moved a predetermined number of times, such as three times, per unit time. The extraction unit 241 may also detect that the user has performed a second action based on signals from force sensors 223 in multiple body parts. For example, the extraction unit 241 determines that a second action has occurred if it detects that forces have been applied twice per unit time based on the electrical signal from the force sensor 223 included in the upper arm sensor 217, and then that forces have been applied three times per unit time based on the electrical signal from the force sensor 223 included in the thigh sensor 218. In other words, the second action is an action in which the user first moves the upper arm muscles twice per unit time, and then moves the thigh muscles three times per unit time. The extraction unit 241 emits a block sign when the muscles of one or more parts of the body are moved. Based on its own determination result, the extraction unit 241 generates an instruction signal indicating an instruction to the instruction target. The instruction signal may include the sensing information itself. The extraction unit 241 may input the signal information constituting the block sign into a neural network using an action estimation model generated in advance by machine learning, and determine the action based on the action determination result information output as a result.

[0036] The motion determination model may be generated in advance by the control device 20 or other devices, for example. The motion determination model is, as an example, data such as the weight coefficients of a neural network generated by machine learning a combination of signals indicating muscle movement and correct data of the corresponding motion.

[0037] The processing of the extraction unit 241 described above is one aspect of the process in which the integrated control unit 24 extracts a series of signals indicating a target movement from among the signals indicating muscle movement from sensors attached to one or more predetermined parts of the body, and transmits the series of signals indicating the target movement to the target.

[0038] Even if the sensing information does not indicate a block sign, the extraction unit 241 outputs the sensing information to the motion estimation unit 242 and the fatigue level estimation unit 243. The motion estimation unit 242 estimates the user's actions that are not block signs (step S103). For example, it estimates whether the user is walking, running, stopped, crouching, crawling, going uphill, or going down stairs based on signals such as muscle movement and joint movement (angle, angular velocity, acceleration, etc.) included in the sensing information. The fatigue level estimation unit 243 estimates the user's fatigue level based on signals such as muscle movement and joint movement (angle, angular velocity, acceleration, etc.) included in the sensing information, the motion estimation signal estimated by the motion estimation unit 242, and the user's vital signals (step S104). In estimating fatigue levels, the system may estimate based on signals indicating muscle movement or joint movement (angle, angular velocity, acceleration, etc.) that shows block signs, or it may estimate based on signals indicating muscle movement or joint movement (angle, angular velocity, acceleration, etc.) that does not show block signs. Alternatively, the system may estimate based on motion estimation signals such as walking, running, and stopping estimated by the motion estimation unit 242. Furthermore, the fatigue level estimation unit 243 may estimate fatigue levels based on signals indicating the user's vital signs such as heart rate, body temperature, and sweating.

[0039] The fatigue level estimation unit 243 estimates a high level of fatigue when it determines, for example, that a signal indicates that the user's walking speed is slower than at the start of their activity, based on sensing information output from the inertial sensor 221 and angular velocity sensor 222 of the hip joint sensor 211. The fatigue level may be information that expresses the degree of fatigue of the user numerically. The fatigue level estimation unit 243 may also input the signal information sensed by the inertial sensor 221 and angular velocity sensor 222 into a neural network using a fatigue level estimation model generated in advance by machine learning, and estimate the fatigue level based on the fatigue level estimation result output as a result.

[0040] The fatigue level estimation model may be generated in advance by, for example, the control device 20 or other device. The fatigue level estimation model may, as an example, be data such as the weight coefficients of a neural network generated by machine learning a combination of signals indicating muscle movement or joint movement and correct fatigue level data corresponding to those signals.

[0041] The signal generation unit 245 generates transmission information including the instruction signal generated by the extraction unit 241, the operation estimation signal indicating the operation estimated by the operation estimation unit 242 based on the signal that does not show a block sign, and the fatigue level estimation signal based on the results estimated by the fatigue level estimation unit 243 (step S105). The integrated control unit 24 transmits the transmission information to the unmanned vehicle 30 via the communication unit 23 (step S106).

[0042] In the process described above, the control device 20 transmits instruction signals, motion estimation signals, and fatigue level estimation signals generated based on the block sign signals to the unmanned vehicle 30. However, the control device 20 may transmit the signals containing each sensing information acquired by the information acquisition unit 25 to the unmanned vehicle 30 as is. In this case, the block sign recognition unit 343 of the unmanned vehicle 30 may detect the signal indicating the block sign and generate an instruction signal, similar to the instruction signal generation process described above. In this case, the fatigue level recognition unit 344 of the unmanned vehicle 30 may generate a fatigue level estimation signal in the same manner as the process described above. The unmanned vehicle 30 may also have a function equivalent to the motion estimation unit 242 described above, and estimate motion based on signals including each sensing information. As a result, the transmission information sent from the control device 20 to the unmanned vehicle 30 includes only signals indicating voltage values ​​and other sensing information from each sensor acquired by the information acquisition unit 25 of the control device 20. By transmitting such information from the control device 20 to the unmanned vehicle 30, even if the communication is intercepted, the intended content of the signal cannot be determined from the voltage value information detected by the sensors alone, thus enabling highly secure communication between the control device 20 and the unmanned vehicle 30. The information transmitted from the control device 20 to the unmanned vehicle 30 may be encrypted. Similarly, the information transmitted from the unmanned vehicle 30 to the control device 20 may also be encrypted.

[0043] Here, the integrated control unit 24 may, before transmitting the transmission information to the unmanned vehicle 30, ask the user to confirm whether the instruction signals included in the transmission information are correct, and only transmit the transmission information including those instruction signals to the unmanned vehicle 30 if the user confirms that they are correct. For example, the integrated control unit 24 drives the drive devices 270, such as the arm solenoid 271 and the shin solenoid 272, based on the operation determined by the extraction unit 241. The user confirms whether the action determined by the extraction unit 241 is correct based on the movement of the drive unit 270, and inputs the result by moving the muscles of a predetermined part of the body. The extraction unit 241 extracts a block sign signal based on the sensing information and determines whether the determined action is correct. For example, suppose that a user applying force to their upper arm three times in a predetermined time unit is a sign that the action is correct. In this case, the extraction unit 241 detects the signal that the user has applied force to their upper arm three times in a predetermined time unit and recognizes that the action is correct based on the user applying force to their upper arm three times in a predetermined time unit. If the extraction unit 241 determines that the operation is correct, it generates an instruction signal indicating approval, and the integrated control unit 24 transmits the transmission information including that signal to the unmanned vehicle 30.

[0044] The communication unit 33 of the unmanned vehicle 30 receives transmission information including an instruction signal, an operation estimation signal, and a fatigue level estimation signal (step S107). The integrated control unit 34 acquires instruction signals, operation estimation signals, and fatigue level estimation signals from the transmitted information. The block sign recognition unit 343 recognizes block signs based on the instruction signals (step S108). In parallel, the fatigue level recognition unit 344 obtains a fatigue level estimation result from the fatigue level estimation signal and recognizes the user's current fatigue level. The fatigue level recognition unit 344 may also estimate the fatigue level based on the fatigue level estimation signal, similar to the control device 20 of the powered suit 10, and recognize the user's current fatigue level. The fatigue level prediction unit 345 predicts the future increase or decrease in the user's fatigue level based on the user's current fatigue level and the route plan showing the user's future movement route indicated by the route planning unit 346. The environment recognition unit 341 generates environmental information based on sensing information obtained from the sensing device 300. The environmental information may include information such as weather, distance to obstacles, and temperature. The self-position estimation unit 342 calculates the position (latitude, longitude, altitude) of the unmanned vehicle 30 based on sensing information from the GPS sensor 318.

[0045] The block sign recognition unit 343 then instructs the route planning unit 346 to start processing if the block sign indicates an instruction to create a route plan. The route planning unit 346 creates a route plan showing the user's future travel route based on environmental information, the current position of the unmanned vehicle 30, the user's fatigue level, and destination location information and map information obtained from the memory unit 32 (step S109). The instruction signal may also include the user's location information measured by the control device 20, and the route plan may be created based on this location information.

[0046] The route planning unit 346 creates route planning information based on the current location information, destination location information, map information, and the user's fatigue level. The route planning information may be information indicating the route from the current location to the destination. The route planning unit 346 calculates multiple routes from the current location to the destination using known route estimation processing, and calculates the distance to the destination for each of those routes and the elevation difference indicated by the route. The route planning unit 346 selects one of the multiple routes based on the fatigue level. For example, if the user's fatigue level is high, the route planning unit 346 selects the route with the smallest elevation difference between the highest and lowest coordinates in the route. The route planning unit 346 outputs the selected route information to the signal generation unit 347.

[0047] Furthermore, the fatigue level prediction unit 345 predicts the future increase or decrease in the user's fatigue level based on the user's current fatigue level and the route plan indicating the user's future travel route shown by the route planning unit 346. The fatigue level prediction unit 345 outputs the predicted fatigue level information to the signal generation unit 347.

[0048] The signal generation unit 347 generates a response signal including route information and fatigue level prediction information, and transmits it to the control device 20 via the communication unit 33 (step S110). This process is one aspect of the process by which the response means of the unmanned vehicle 30 transmits a signal indicating an instruction response generated based on the user's fatigue level to the control device 20. The route information may, for example, be information indicating the direction of movement, such as left or right, when approaching a fork in the road.

[0049] Figure 8 is a second diagram showing the processing flow of the control system. The communication unit 23 of the control device 20 receives a response signal. The integrated control unit 24 acquires the response signal (step S201). The integrated control unit 24 outputs the response signal to the signal recognition unit 244. The signal recognition unit 244 recognizes the path information and fatigue prediction information contained in the response signal (step S202). The signal recognition unit 244 outputs the path information and fatigue prediction information to the haptics control unit 27. The haptics control unit 27 controls the drive device 270 based on the path information and fatigue prediction information (step S203). For example, if the path information indicates a rightward direction, the haptics control unit 27 controls the drive device 270 to perform an action indicating a rightward direction. For example, the haptics control unit 27 controls the piston motion of the arm solenoid 271 to be repeated twice. The user moves to the right when the tip of the piston touches the user's skin indirectly or directly twice.

[0050] Furthermore, the haptics control unit 27 controls the drive unit 270 to indicate a significant increase in fatigue level if the predicted increase or decrease in future fatigue level after selecting the aforementioned path is significant. For example, the haptics control unit 27 controls the piston motion of the shin solenoid 272 five times. If the tip of the piston touches the user's skin five times, either indirectly or directly, the user recognizes that there is a risk of a significant increase in future fatigue level if the aforementioned path is selected. The user can use this risk as one of the factors in deciding whether or not to approve the aforementioned path information.

[0051] The route information may further include information for movement control, and the haptics control unit 27 may, based on the route information, include information such as, for example, moving 1 km in the rightward direction at a speed of 5 km / h. The haptics control unit 27 may convert the route information into arbitrary haptics information agreed upon in advance with the user, and generate a haptics control signal indicating that information to control the drive unit 270. The route information may also be information indicating a route number. The signal recognition unit 244 detects a number indicating a predetermined route from among the pre-set routes based on the route information included in the response signal. The haptics control unit 27 applies an action to the drive unit 270 according to the route number. As a result, the user recognizes the route number and moves in the direction of that route. Alternatively, the route information included in the response signal may be the route information of the unmanned vehicle 30.

[0052] In this case, the user may decide whether or not to agree with the routing information included in the response signal and notify the control device 20 of this information by moving the muscles of a predetermined part of the body. The extraction unit 241 extracts a block sign from the sensing information that indicates the user has moved the muscles of a predetermined part of the body, and determines whether or not the extracted block sign is an action in favor of the action (step S204). This determination of whether or not to agree may be made within a predetermined time after the drive device 270 is driven based on the response signal. If the extraction unit 241 determines that the sensing information indicates an action in favor of the action, it generates an instruction signal indicating that it agrees, and the integrated control unit 24 transmits the transmission information including the instruction signal to the unmanned vehicle 30 via the communication unit 23 (step S205).

[0053] The communication unit 33 of the unmanned vehicle 30 acquires the transmission information. The block sign recognition unit 343 recognizes the information indicating approval included in the instruction signal extracted from the transmission information (step S206). The block sign recognition unit 343 outputs the information indicating approval to the vehicle control unit 36. The vehicle control unit 36 ​​acquires route information from the route planning unit 346. Based on the route information and the current location information obtained from the GPS sensor 318, the vehicle control unit 36 ​​controls the steering wheel, which is the drive unit 37, and the speed of the unmanned vehicle 30 so that the unmanned vehicle 30 moves along the route indicated by the route information (step S207).

[0054] Through the above process, a user wearing the powered suit 10 can issue instructions to the unmanned vehicle 30 through the powered suit 10 using only muscle movements as block signals. The unmanned vehicle 30 can also communicate responses to the user using haptic technology. As a result, the user can perform highly confidential tasks without using gestures or voice, and without others being able to perceive the control status or operation of the unmanned vehicle 30.

[0055] Furthermore, the response signal transmitted from the unmanned vehicle 30 to the control device 20 may include the haptics control signal described above. This eliminates the need for the haptics control unit 27 to convert the information transmitted from the unmanned vehicle 30 into a haptics control signal. Additionally, when the response signal includes a haptics control signal, even if the signal is intercepted, its intended meaning cannot be determined, thus enabling highly secure communication.

[0056] The unmanned vehicle 30 described above may be a vehicle that leads the user or a vehicle that follows the user. In the above example, the unmanned vehicle 30 transmits a response signal containing route information to the control device 20. However, the control device 20 may transmit an instruction signal to request another response based on the movement of muscles in the user's body parts, and the unmanned vehicle 30 may transmit a response signal to the control device 20 containing other response information corresponding to that instruction signal.

[0057] In the example described above, the control device 20 extracts a signal corresponding to a block sign based on the user's muscle movements. However, the control device 20 may also extract a signal corresponding to a block sign based on sensing information other than muscle movements, which is sensed by other sensors provided on the powered suit 10. For example, a head-mounted device, which is part of the powered suit 10, may sense the user's eye movements or eyelid movements, and the control device may extract a block sign based on this sensing information.

[0058] Figure 9 is a second diagram showing the schematic configuration of the control system. The control system 100 described above may be configured such that, instead of the unmanned vehicle 30 which is an example of an instruction and analysis device, an unmanned aerial vehicle (UAV) such as a drone 50 communicates wirelessly with the control device 20. In this case, the UAV performs the same processing as the unmanned vehicle 30. The instruction and analysis device may also be a device composed of multiple unmanned vehicles or UAVs.

[0059] Figure 10 is a third diagram showing the schematic configuration of the control system. Furthermore, the control system 100 described above may be configured by communicating with a terminal device 60 such as a PC (Personal Computer) or a cloud server, instead of the unmanned vehicle 30 which is an example of an instruction and analysis device. In this case, the terminal device 60 or the cloud server may have the functions of the integrated control unit 34 of the unmanned vehicle 30 and transmit response signals to the control device 20. Alternatively, an operator located on the other side of the PC or cloud server may transmit response signals to the control device 20.

[0060] The block signs described above may also be used as passwords. For example, the control device 20 may transmit a specific block sign as a password sign to an instruction analysis device, etc. This may cause the instruction analysis device, etc., to activate based on the received password sign signal.

[0061] In the above description, the extraction unit 241 of the control device 20 extracts a signal indicating an instruction for a target based on a signal indicating muscle movement in a predetermined part of the user's body. However, the sensing information from each sensor 210 may be transmitted to an unmanned vehicle 30, a terminal device 60, a cloud server, etc., and these receiving devices may perform processing equivalent to that of the extraction unit 241. In this way, some of the functions of the control device 20 may be possessed by the connected device that communicates with the control device 20.

[0062] Figure 11 shows the minimum configuration of the control device. Figure 12 shows the processing flow of a control device with a minimum configuration. The control device 20 may include at least an acquisition means 810, an extraction means 820, and a transmission means 830. The acquisition means 810 acquires signals indicating muscle movement in a predetermined part of the body of the user wearing the powered suit 10 (step S901). The extraction means 820 extracts a signal indicating an instruction for the instruction target based on a signal indicating the movement of muscles in a predetermined part of the user's body (step S902). The transmitting means 830 transmits a signal to the target of instruction indicating an instruction to the target of instruction (step S903).

[0063] (Hardware configuration) Figure 13 is a schematic block diagram showing an example of the hardware configuration of a computing processing unit 80 capable of realizing the control device 20 (or instruction and analysis device such as an unmanned vehicle 30) according to each embodiment of the present invention. This section describes an example of hardware resource configuration for implementing a control device 20 (or an instruction and analysis device such as an unmanned vehicle 30) using a single computing device (information processing device, computer). However, such a control device 20 (or an instruction and analysis device such as an unmanned vehicle 30) may be implemented using at least two computing devices, either physically or functionally. Furthermore, such a control device 20 (or an instruction and analysis device such as an unmanned vehicle 30) may be implemented as a dedicated device.

[0064] The computing device 80 includes a central processing unit (CPU) 81, a volatile storage device 82, a disk 83, a non-volatile recording medium 84, and a communication interface (hereinafter referred to as "communication IF") 87. The computing device 80 may be connectable to an input device 85 and an output device 86. The computing device 80 can send and receive information with other computing devices and communication devices via the communication IF 87.

[0065] The non-volatile recording medium 84 is a computer-readable medium, such as a Compact Disc or a Digital Versatile Disc. Alternatively, the non-volatile recording medium 84 may be a Universal Serial Bus memory (USB memory), a Solid State Drive, or the like. The non-volatile recording medium 84 can hold the program without power supply, making it portable. The non-volatile recording medium 84 is not limited to the media described above. Furthermore, instead of the non-volatile recording medium 84, the program may be carried via the communication interface 87 and a communication network. The volatile memory device 82 is computer-readable and can temporarily store data. The volatile memory device 82 is a type of memory such as DRAM (dynamic random access memory) or SRAM (static random access memory).

[0066] In other words, the CPU 81 copies the software program (computer program; hereinafter simply referred to as "program") stored on disk 83 to the volatile storage device 82 when executing it, and then performs arithmetic processing. The CPU 81 reads the data necessary for program execution from the volatile storage device 82. When display is required, the CPU 81 displays the output result on the output device 86. When a program is input from an external source, the CPU 81 reads the program from the input device 85. The CPU 81 interprets and executes the analysis program (Figure 4 or Figure 5) in the volatile storage device 82 corresponding to the function (process) represented by each part shown in Figure 2 (or Figure 3). The CPU 81 executes the processing described in each embodiment of the present invention described above. In other words, in such cases, each embodiment of the present invention can be considered to be achievable by such analysis program. Furthermore, each embodiment of the present invention can also be considered to be achievable by a computer-readable non-volatile recording medium on which such analysis program is recorded.

[0067] The present invention has been described above using the embodiments described above as exemplary examples. However, the present invention is not limited to the embodiments described above. That is, the present invention can be applied in various forms that can be understood by those skilled in the art, within the scope of the present invention. [Explanation of symbols]

[0068] 10. Powered Suit 20. Control device 21...Power supply section 22...Storage section 23. Communications Department 24. Integrated Control Unit 25...Information acquisition unit (acquisition means) 26. Actuator Control Unit 27. Haptics Control Unit 241...Extraction unit (extraction means) 242...Motion estimation section 243... Fatigue level estimation unit 244...Signal recognition section 245...Signal generation unit 30... Unmanned vehicles 31...Power supply section 32...Storage section 33. Communications Department (Transmission Method) 34. Integrated Control Unit 35...Information acquisition department 36. Vehicle Control Unit 37. Drive unit 341...Environmental recognition department 342... Self-position estimation section 343... Block sign recognition unit 344... Fatigue level recognition unit 345... Fatigue level prediction unit 346...Route Planning Department 347...Signal generation unit 40...battery 50... Drones 60... Terminal device

Claims

1. An acquisition means for acquiring signals indicating muscle movement in a predetermined part of the body of a user wearing a powered suit, An extraction means for extracting a signal indicating an instruction to an instruction target based on a signal indicating muscle movement in a predetermined part of the user's body, A transmitting means for transmitting a signal indicating an instruction to the instruction target to the instruction target, A receiving means that receives a signal indicating the direction of movement in an instruction response from the instruction target based on the transmission of a signal indicating the movement of the instruction to the instruction target, A control means for driving a drive device provided in the powered suit based on a signal indicating the direction of movement, A control device equipped with the following features.

2. The acquisition means acquires signals indicating muscle movement from sensors provided in the powered suit that sense the movement of muscles in the body parts. The control device according to claim 1.

3. The acquisition means acquires signals indicating muscle movement from one or more sensors attached to predetermined parts of the body. The extraction means extracts a continuous signal indicating the instructed movement from among the signals indicating the movement of the muscle, from one or more sensors attached to a predetermined part of the body. The transmitting means transmits a series of signals indicating the movement of the instruction to the instruction target. The control device according to claim 1 or claim 2.

4. It comprises a control device and an instruction and analysis device, The control device is An acquisition means for acquiring signals indicating muscle movement in a predetermined part of the body of a user wearing a powered suit, An extraction means for extracting a signal indicating an instruction to an instruction target based on a signal indicating muscle movement in a predetermined part of the user's body, A transmitting means for transmitting a signal indicating an instruction to the instruction target to the instruction target, A receiving means that receives a signal indicating the direction of movement in an instruction response from the instruction target based on the transmission of a signal indicating the movement of the instruction to the instruction target, A control means for driving a drive device provided in the powered suit based on a signal indicating the direction of movement, Equipped with, The instruction analysis device, which is the target of the instruction, A response means that generates a signal indicating the instruction response in the direction of movement based on a signal indicating the movement of the instruction, A control system equipped with the following features.

5. The instruction and analysis device described above is The system includes a calculation means for calculating the user's fatigue level based on a signal indicating the movement of the aforementioned instruction, The response means transmits a signal indicating the instruction response generated based on the fatigue level to the control device. The control system according to claim 4.

6. The response means of the instruction analysis device generates planning information for the user's route based on the fatigue level and transmits a signal indicating the instruction response, including the planning information for the route, to the control device. The control system according to claim 5.

7. The control device The system acquires signals indicating muscle movement in specific parts of the body of a user wearing a powered suit. Based on signals indicating muscle movement in a predetermined part of the user's body, a signal indicating an instruction for the instruction target is extracted. A signal indicating an instruction for the target of the instruction is transmitted to the target of the instruction. A receiving means that receives a signal indicating the direction of movement in an instruction response from the instruction target based on the transmission of a signal indicating the movement of the instruction to the instruction target, A control means for driving a drive device provided in the powered suit based on a signal indicating the direction of movement, Control method.

8. The control unit's computer, A means for acquiring signals that indicate the movement of muscles in a predetermined part of the body of a user wearing a powered suit. Extraction means for extracting a signal indicating an instruction to an instruction target based on a signal indicating muscle movement in a predetermined part of the user's body. A transmitting means that transmits a signal indicating an instruction to the instruction target to the instruction target, Receiving means that receive a signal from the target of instruction indicating the direction of movement based on the transmission of a signal indicating the movement of the instruction to the target of instruction, Control means for driving a drive device provided in the powered suit based on the signal indicating the direction of movement, A program that makes it function as such.

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