Lower limb power-assisted exoskeleton gait recognition and power-assisted control system and method

Abstract

The invention relates to the technical field of exoskeletons, and discloses a lower limb assistance exoskeleton gait recognition and assistance control system and method. The system comprises a joint motion information acquisition module used for measuring joint motion information; the gait phase estimation module is used for carrying out gait phase judgment according to the joint movement information so as to determine a current gait phase; the joint angular position control module is used for adopting a joint angular position control mode to control the exoskeleton system when the current gait phase is in the supporting phase; and the joint torque control module is used for adopting a joint torque control mode to control the exoskeleton system when the current gait phase is in the swing phase. According to the system, independent control over the swing phase gait and the supporting phase gait is achieved through the system, active assistance can be achieved through the independent control mode under different gait phases, the man-machine following performance can be improved, then the wearing comfort of the exoskeleton is improved, and therefore the system adapts to the outdoor electric power overhaul occasion; and the burden of an electric power overhaul worker is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of exoskeletons, and in particular to a lower limb power-assisted exoskeleton gait recognition and power-assisted control system and method. Background Art

[0002] In terms of exoskeleton sensing and control technology, exoskeleton robots can be used to reduce the burden of power maintenance workers. Existing exoskeleton systems usually adopt sensing and control solutions based on joint angle encoders, gait recognition and control solutions based on plantar pressure sensing, and biological sensing and control solutions based on surface electromyography (sEMG). Among them, the sensing solution based on joint angle encoders has the advantage of simple operation, but the equipment recognition accuracy is low. At the same time, it is installed on the exoskeleton instead of the human body, which makes the algorithm not suitable for the human body and cannot accurately and smoothly track the human body; the gait recognition and control solution based on plantar pressure sensing has the advantages of high real-time gait sensing and recognition and simple gait recognition algorithm, but it is necessary to equip the exoskeleton system with an additional pair of sensor shoes, which is inconvenient to put on and take off and has poor adaptability; the biological sensing and control solution based on surface electromyography (sEMG) has the advantage of more timely perception of human movement intentions, but the surface electromyography signal is weak and easily interfered, resulting in poor measurement reliability and large measurement differences between different individuals. These factors limit the use of this solution in outdoor power maintenance occasions.

[0003] In view of the characteristics and shortcomings of the above schemes, the researchers proposed a perception and control scheme that uses the fusion of multiple sensor measurement data. However, this brings the following problems: multiple sensor measurement devices make the wearability of the entire exoskeleton system worse, which increases the complexity and time of wearing the exoskeleton system on the one hand, and interferes with other work equipment on the body on the other hand; the multi-sensor data fusion algorithm increases the time for processing perception decision data, resulting in a lag in the response of the exoskeleton system, and the mismatch between the movements of the exoskeleton and the wearer affects the assistance effect. Summary of the invention

[0004] The main purpose of the present invention is to provide a lower limb assisted exoskeleton gait recognition and assistance control system and method, aiming to solve at least one of the above-summarized problems.

[0005] To achieve the above object, the present invention provides a lower limb power-assisted exoskeleton gait recognition and power-assisted control system, comprising:

[0006] A joint motion information acquisition module, used for measuring joint motion information and outputting the joint motion information to a gait phase estimation module, a joint angle position control module and a joint torque control module respectively;

[0007] The gait phase estimation module is used to perform gait phase judgment according to the joint motion information to determine the current gait phase;

[0008] The joint angle position control module is used to control the exoskeleton system using a joint angle position control mode when the current gait phase is in the stance phase;

[0009] The joint torque control module is used to control the exoskeleton system in a joint torque control mode when the current gait phase is in the swing phase.

[0010] In some embodiments, the joint motion information acquisition module is specifically used to measure the joint angular position, angular velocity and angular acceleration based on an inertial sensor to obtain a joint angle signal, a joint angular velocity signal and a joint angular acceleration signal; and generate joint motion information according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal.

[0011] In some embodiments, the gait phase estimation module is further used to receive plantar pressure data transmitted by a plantar pressure sensor;

[0012] The gait phase estimation module is specifically used to determine the gait phase according to the joint motion information to obtain an initial gait phase;

[0013] The support-related joint angle threshold and the swing-related joint angle threshold are calibrated according to the plantar pressure data, and the initial gait phase determined based on the joint motion information is calibrated and aligned to determine the current gait phase.

[0014] In some embodiments, the joint angle position control module is specifically used to use the joint angle position control mode to take the joint motion information as feedback and servo-control the exoskeleton system according to the angle position curve to generate active power support when the current gait phase is in the support phase.

[0015] In some embodiments, the joint torque control module is used to use the joint torque control mode to perform auxiliary torque control on the exoskeleton system according to the joint motion information combined with the human-machine dynamics model when the current gait phase is in the swing phase, so as to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

[0016] In addition, to achieve the above-mentioned purpose, the present invention also proposes a method for gait recognition and power-assisted control of a lower limb power-assisted exoskeleton, comprising:

[0017] Measuring joint motion information;

[0018] Performing gait phase judgment according to the joint motion information to determine the current gait phase;

[0019] When the current gait phase is in the stance phase, the exoskeleton system is controlled using the joint angle position control mode;

[0020] When the current gait phase is in the swing phase, the exoskeleton system is controlled using the joint torque control mode.

[0021] In some embodiments, when the current gait phase is in the stance phase, controlling the exoskeleton system using the joint angle position control mode includes:

[0022] When the current gait phase is in the stance phase, a preset reference assisting joint angle waveform is used as a reference waveform and the joint motion information is used as feedback;

[0023] generating a control signal based on a deviation between the reference waveform and the fed-back data;

[0024] Based on the position servo controller, according to the control signal and the angular position curve, the exoskeleton system is servo-controlled to generate active power support.

[0025] In some embodiments, the joint angle position control algorithm adopted by the position servo controller is:

[0026]

[0027] Where τ is the output torque of the joint motor; Δθ = θ d -θ is the joint angle deviation; θ d is the expected joint angle; ΣΔθ is the historical accumulated joint angle deviation; is the joint angular velocity deviation; K p K is the proportional control gain of the joint angle controller; i K is the integral control gain of the joint angle controller; d is the differential control gain of the joint angle controller; τ ff is the feedforward torque compensation term, which is used to compensate for joint friction and damping.

[0028] In some embodiments, when the current gait phase is in the swing phase, controlling the exoskeleton system using the joint torque control mode includes:

[0029] When the current gait phase is in the swing phase, determining a joint angle signal, a joint angular velocity signal, and a joint angular acceleration signal according to the joint motion information;

[0030] Based on the human-machine dynamics model, the output torque of the joint motor is obtained according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal;

[0031] Based on the motor current loop servo control algorithm, a control signal is generated through a current loop controller according to the deviation between the torque motor current and the reference value of the current loop control loop;

[0032] The exoskeleton system is subjected to auxiliary torque control based on the control signal, so as to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

[0033] In some embodiments, the torque generator of the human-machine dynamics model is expressed as:

[0034]

[0035] Among them, θ is the joint angle signal; Joint angular velocity signal; Joint angular acceleration signal; H(θ) is the inertia matrix; is the Coriolis force matrix; F(θ) is the friction matrix; G(θ) is the gravity matrix; τ ω is the wearer’s torque; τ is the output torque of the joint motor;

[0036] Reference current I d for:

[0037]

[0038] Among them, K s is the motor torque coefficient;

[0039] The expression of the motor current loop servo control algorithm is:

[0040] U=K Ip ΔI+K Ii ΣΔI+K Id (ΔI-ΔI a )

[0041] Where I is the torque motor current; ΔI=I d -I is the current deviation value at the current moment, ∑ΔI is the historical accumulated current deviation value, ΔI a is the current deviation value at the previous moment, K Ip is the proportional control gain of the current controller; K Ii is the current controller integral control gain, K Id is the current controller derivative control gain.

[0042] The present invention proposes a lower limb power-assisted exoskeleton gait recognition and power-assisted control system, comprising: a joint motion information acquisition module, used to measure joint motion information and output the joint motion information to a gait phase estimation module, a joint angle position control module and a joint torque control module; the gait phase estimation module, used to perform gait phase judgment according to the joint motion information to determine the current gait phase; the joint angle position control module, used to control the exoskeleton system using a joint angle position control mode when the current gait phase is in the support phase; the joint torque control module, used to control the exoskeleton system using a joint torque control mode when the current gait phase is in the swing phase. In the present invention, the lower limb power-assisted exoskeleton gait recognition and power-assisted control system realizes independent control of the swing phase gait and the support phase gait respectively. Compared with the traditional full gait cycle control mode, the independent control mode under different gait phases can not only realize active power assistance but also improve the following performance between man and machine, thereby improving the wearing comfort of the exoskeleton, so as to adapt to outdoor power maintenance occasions and reduce the burden of power maintenance workers. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a structural block diagram of an embodiment of a lower limb power-assisted exoskeleton gait recognition and power-assisted control system of the present invention;

[0044] Figure 2 A schematic diagram of the human body gait phase division principle involved in the embodiment of the present invention;

[0045] Figure 3 This is a block diagram of a joint angle position control mode involved in an embodiment of the present invention;

[0046] Figure 4 It is a block diagram of the joint torque control mode involved in the embodiment of the present invention;

[0047] Figure 5 A schematic diagram of the lower limb exoskeleton structure involved in an embodiment of the present invention;

[0048] Figure 6 A schematic diagram of the flow of the lower limb power-assisted exoskeleton gait recognition and power-assisted control method of the present invention;

[0049] Figure 7 The present invention is a schematic diagram of the structure of an electronic device in a hardware operating environment according to an embodiment of the present invention.

[0050] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0053] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] The present invention provides a lower limb power-assisted exoskeleton gait recognition and power-assisted control system and method.

[0055] Reference Figure 1 , Figure 1 This is a structural block diagram of an embodiment of a lower limb power-assisted exoskeleton gait recognition and power-assisted control system of the present invention.

[0056] like Figure 1 As shown, the lower limb power-assisted exoskeleton gait recognition and power-assisted control system includes:

[0057] A joint motion information acquisition module, used for measuring joint motion information and outputting the joint motion information to a gait phase estimation module, a joint angle position control module and a joint torque control module respectively;

[0058] The gait phase estimation module is used to perform gait phase judgment according to the joint motion information to determine the current gait phase;

[0059] The joint angle position control module is used to control the exoskeleton system using a joint angle position control mode when the current gait phase is in the stance phase;

[0060] The joint torque control module is used to control the exoskeleton system in a joint torque control mode when the current gait phase is in the swing phase.

[0061] It can be understood that this embodiment uses a lower limb exoskeleton (lower limb exoskeleton robot) for assisting power maintenance as an example to illustrate the module structure of the control system. The lower limb exoskeleton includes the lower limb power-assisted exoskeleton gait recognition and power-assisted control system as described in the embodiment of the present invention.

[0062] In one embodiment, the joint motion information acquisition module is specifically used to measure the joint angular position, angular velocity and angular acceleration based on an inertial sensor to obtain a joint angle signal, a joint angular velocity signal and a joint angular acceleration signal; and generate joint motion information according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal.

[0063] Specifically, the joint motion information acquisition module can use inertial sensors to measure joint angle position, velocity, and acceleration, and the inertial sensor output signals are transmitted to the gait phase estimation module, the joint angle position control module, and the joint torque control module respectively.

[0064] In one embodiment, the gait phase estimation module is also used to receive plantar pressure data transmitted by the plantar pressure sensor; the gait phase estimation module is specifically used to judge the gait phase according to the joint motion information to obtain the initial gait phase; calibrate the support-related joint angle threshold and the swing-related joint angle threshold according to the plantar pressure data, and calibrate and align the initial gait phase judged based on the joint motion information to determine the current gait phase.

[0065] Specifically, the gait phase estimation module receives data (joint motion information) from the joint motion information acquisition module, such as Figure 2 As shown, the gait phase estimation module determines the current gait phase according to the joint angle, angular velocity, and angular acceleration, and divides the current gait phase into a support phase and a swing phase. In this embodiment, the sensor of the lower limb exoskeleton also includes a plantar pressure sensor, which is used to measure plantar pressure information. The output plantar pressure data is transmitted to the gait phase estimation module to calibrate and align the gait phase estimation based on the joint motion information.

[0066] Specifically, the gait phase estimation module also receives plantar pressure data from the plantar pressure sensor, uses the plantar pressure data to calibrate the support-related joint angle threshold and the swing-related joint angle threshold, and calibrates and aligns the gait phase estimation module based on joint motion information.

[0067] It should be noted that the plantar pressure sensor is only used during initial threshold calibration and adjustment, and the plantar pressure sensor is removed during normal walking.

[0068] In this embodiment, by using inertial sensors to sense gait phase and plantar pressure correction, the sensor configuration is simplified, the reliability and rapidity of the sensor perception system in the exoskeleton system are improved, and the wearability of other equipment of the exoskeleton system is not affected.

[0069] In one embodiment, the joint angle position control module is specifically used to use the joint angle position control mode to take the joint motion information as feedback and servo-control the exoskeleton system according to the angle position curve to generate active power support when the current gait phase is in the support phase.

[0070] Specifically, the gait phase estimation module receives the data (joint motion information) from the joint motion information acquisition module, and the gait phase estimation module determines the gait phase according to the joint angle, angular velocity, and angular acceleration in the joint motion information, so as to divide the gait phase into a support phase and a swing phase. When the gait phase estimation module determines that the current gait phase is in the support phase, the joint angle position control mode is adopted, and the joint angle position control module uses the joint motion information as feedback and performs servo control according to the established angle position curve, so that the exoskeleton system generates active power support.

[0071] Exemplarily, when the gait phase estimation module determines that the current gait phase is in the support phase, the joint angle position control mode is adopted, and the predefined reference power-assisted joint angle waveform is used as the reference given by the joint angle position control module, and the joint motion information is used as feedback. The joint angle position control module generates a control signal based on the deviation between the reference given and the feedback data, and the control signal is then transmitted to the drive and transmission mechanism to drive the wearer's joint movement and generate power-assisted support. The joint angle position control algorithm adopted by the position servo controller is specifically as follows:

[0072]

[0073] Where τ is the output torque of the joint motor; Δθ = θ d -θ is the joint angle deviation; θ d is the expected joint angle; ΣΔθ is the historical accumulated joint angle deviation; is the joint angular velocity deviation; K p K is the proportional control gain of the joint angle controller; i K is the integral control gain of the joint angle controller; d is the differential control gain of the joint angle controller; τ ff is the feedforward torque compensation term, which is used to compensate for joint friction and damping.

[0074] It can be understood that the present embodiment adopts a support-related joint angle position control mode to provide active power support, and a swing phase torque servo control mode to improve the compliance between man and machine. Compared with the traditional full gait cycle control method, this independent control mode under different gait phases can not only achieve active power assistance but also improve the following performance between man and machine, thereby improving wearing comfort.

[0075] In one embodiment, the joint torque control module is used to use the joint torque control mode to perform auxiliary torque control on the exoskeleton system according to the joint motion information combined with the human-machine dynamics model when the current gait phase is in the swing phase, so as to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

[0076] Specifically, when the gait phase estimation module determines that the current gait phase is in the swing phase, the joint torque control mode is adopted. The joint torque control module performs auxiliary torque control based on the joint motion information combined with the human-machine dynamics model to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

[0077] Exemplarily, when the gait phase controller determines that the current gait phase is in the swing phase, the joint torque control mode is adopted, and the joint angle signal θ, the joint angular velocity signal and the joint angular acceleration signal are obtained through the joint motion information acquisition module to obtain the joint desired torque τ (the output torque of the joint motor), and the human-machine dynamics model is used to generate the output torque of the joint motor. The expression of the torque generator of the human-machine dynamics model is:

[0078]

[0079] Among them, θ is the joint angle signal; Joint angular velocity signal; Joint angular acceleration signal; H(θ) is the inertia matrix; is the Coriolis force matrix; F(θ) is the friction matrix; G(θ) is the gravity matrix; τ ω is the wearer's torque; τ is the output torque of the joint motor.

[0080] like Figure 3 and Figure 4 As shown, the torque control method based on motor current loop servo control is adopted:

[0081] Reference current I d for:

[0082]

[0083] Among them, K s is the motor torque coefficient;

[0084] The expression of the motor current loop servo control algorithm is:

[0085] U=K Ip ΔI+K Ii ΣΔI+K Id (ΔI-ΔI a )

[0086] Where I is the torque motor current; ΔI=I d -I is the current deviation value at the current moment, ∑ΔI is the historical accumulated current deviation value, ΔI a is the current deviation value at the previous moment, K Ip is the proportional control gain of the current controller; K Ii is the current controller integral control gain, K Id is the current controller derivative control gain.

[0087] For example, Figure 5 As shown, the lower limb power-assisted exoskeleton includes a backboard integrated module (Ⅰ), a waist connection module (Ⅱ), and a thigh drive module (Ⅲ); the backboard control module (Ⅰ) integrates a processor (such as a Raspberry Pi), a battery, a voltage divider, and a TTL to USB serial port module, the waist structure (Ⅱ) is designed with an adjustable structure, connected to the backboard, and the thigh drive module (Ⅲ) outputs auxiliary torque through a motor direct drive, and is designed with an elastic strap to connect to the human thigh. The lower limb power-assisted exoskeleton gait recognition and power-assisted control system proposed in this embodiment can be integrated into the processor of the backboard control module (Ⅰ). The system not only simplifies the sensor configuration, improves the reliability and rapidity of the perception system, and does not affect the wearability of other devices, but also realizes the active power assistance of the exoskeleton, and can improve the human-machine coupling, which is used to adapt to outdoor power maintenance occasions and reduce the burden on power maintenance workers.

[0088] It should be noted that, in view of the many limitations of the existing exoskeleton system's perception and control solutions based on joint angle encoders, plantar pressure, surface electromyographic signals, and multi-sensor fusion, this embodiment uses the system to achieve independent control of the swing phase gait and the support phase gait, which has the following advantages compared with the existing technology: First, the use of inertial sensors to perceive the gait phase and the plantar pressure correction solution simplifies the sensor configuration, improves the reliability and rapidity of the perception system, and does not affect the wearability of other equipment; second, the support-related joint angle position control mode is adopted to provide active power support, and the swing phase torque servo control mode is adopted to improve the compliance between man and machine. Compared with the traditional full gait cycle control method, this independent control mode under different gait phases can not only achieve active power assistance but also improve the following performance between man and machine, thereby improving the wearing comfort.

[0089] The present embodiment proposes a gait recognition and power-assistance control system for lower limb power-assistance exoskeleton, comprising: a joint motion information acquisition module, used to measure joint motion information and output the joint motion information to a gait phase estimation module, a joint angle position control module and a joint torque control module; the gait phase estimation module, used to judge the gait phase according to the joint motion information to determine the current gait phase; the joint angle position control module, used to control the exoskeleton system by adopting a joint angle position control mode when the current gait phase is in the support phase; the joint torque control module, used to control the exoskeleton system by adopting a joint torque control mode when the current gait phase is in the swing phase. In the present embodiment, the gait recognition and power-assistance control system for lower limb power-assistance exoskeleton realizes independent control of the swing phase gait and the support phase gait respectively. Compared with the traditional full gait cycle control mode, the independent control mode under different gait phases can not only realize active power assistance but also improve the following performance between man and machine, thereby improving the wearing comfort of the exoskeleton, so as to adapt to outdoor power maintenance occasions and reduce the burden of power maintenance workers.

[0090] The embodiment of the present invention provides a method for lower limb power-assisted exoskeleton gait recognition and power-assisted control, referring to Figure 6 , Figure 6 This is a flow chart of an embodiment of a method for lower limb assisted exoskeleton gait recognition and assistance control according to the present invention.

[0091] like Figure 6 As shown, the lower limb power-assisted exoskeleton gait recognition and power-assisted control method includes:

[0092] Step S100: measuring joint motion information;

[0093] Step S200: performing gait phase judgment according to the joint motion information to determine the current gait phase;

[0094] Step S300: When the current gait phase is in the stance phase, the exoskeleton system is controlled using a joint angle position control mode;

[0095] Step S400: When the current gait phase is in the swing phase, the exoskeleton system is controlled using a joint torque control mode.

[0096] In one embodiment, when the current gait phase is in the support phase, a joint angle position control mode is used to control the exoskeleton system, including: when the current gait phase is in the support phase, a preset reference power-assisting joint angle waveform is used as a reference waveform and the joint motion information is used as feedback; a control signal is generated based on the deviation between the reference waveform and the feedback data; and a position servo controller is used to servo-control the exoskeleton system according to the angular position curve based on the control signal to generate active power-assisting support.

[0097] In one embodiment, the joint angle position control algorithm adopted by the position servo controller is:

[0098]

[0099] Where τ is the output torque of the joint motor; Δθ = θ d -θ is the joint angle deviation; θ d is the expected joint angle; ΣΔθ is the historical accumulated joint angle deviation; is the joint angular velocity deviation; K p K is the proportional control gain of the joint angle controller; i K is the integral control gain of the joint angle controller; d is the differential control gain of the joint angle controller; τ ff is the feedforward torque compensation term, which is used to compensate for joint friction and damping.

[0100] In one embodiment, when the current gait phase is in the swing phase, the joint torque control mode is used to control the exoskeleton system, including: when the current gait phase is in the swing phase, determining the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal according to the joint motion information; obtaining the output torque of the joint motor according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal based on the human-machine dynamics model; generating a control signal through a current loop controller according to the deviation between the torque motor current and the current loop control loop reference value based on the motor current loop servo control algorithm; and performing auxiliary torque control on the exoskeleton system based on the control signal to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

[0101] In one embodiment, the torque generator of the human-machine dynamics model is expressed as:

[0102]

[0103] Among them, θ is the joint angle signal; Joint angular velocity signal; Joint angular acceleration signal; H(θ) is the inertia matrix; is the Coriolis force matrix; F(θ) is the friction matrix; G(θ) is the gravity matrix; τ ω is the wearer’s torque; τ is the output torque of the joint motor;

[0104] Reference current I d for:

[0105]

[0106] Among them, K s is the motor torque coefficient;

[0107] The expression of the motor current loop servo control algorithm is:

[0108] U=K Ip ΔI+K Ii ΣΔI+K Id (ΔI-ΔI a )

[0109] Where I is the torque motor current; ΔI=I d -I is the current deviation value at the current moment, ∑ΔI is the historical accumulated current deviation value, ΔI a is the current deviation value at the previous moment, K Ip is the proportional control gain of the current controller; K Ii is the current controller integral control gain, K Id is the current controller derivative control gain.

[0110] This embodiment measures joint motion information; performs gait phase judgment based on the joint motion information to determine the current gait phase; when the current gait phase is in the support phase, the exoskeleton system is controlled using the joint angle position control mode; when the current gait phase is in the swing phase, the exoskeleton system is controlled using the joint torque control mode. In this embodiment, the lower limb power-assisted exoskeleton gait recognition and power-assisted control system realizes independent control of the swing phase gait and the support phase gait. Compared with the traditional full gait cycle control method, the independent control mode under different gait phases can not only realize active power assistance but also improve the following performance between humans and machines, thereby improving the wearing comfort of the exoskeleton, so as to adapt to outdoor power maintenance occasions and reduce the burden on power maintenance workers.

[0111] It should be noted that the technical details that are not described in detail in the embodiment of the lower limb assisted exoskeleton gait recognition and assisted control method can be found in any embodiment of the present invention applied to the lower limb assisted exoskeleton gait recognition and assisted control system as described above, and will not be repeated here.

[0112] In addition, an embodiment of the present invention also proposes a storage medium, on which a lower limb assisted exoskeleton gait recognition and assisted control program is stored. When the lower limb assisted exoskeleton gait recognition and assisted control program is executed by a processor, the steps of the lower limb assisted exoskeleton gait recognition and assisted control method as described above are implemented.

[0113] Reference Figure 7 , Figure 7 The figure is a schematic diagram of the structure of an electronic device of the hardware operating environment involved in the embodiment of the present invention.

[0114] like Figure 7As shown, the electronic device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM memory) or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0115] Those skilled in the art will understand that Figure 7 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0116] like Figure 7 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a lower limb power-assisted exoskeleton gait recognition and power-assisted control program.

[0117] exist Figure 7 In the electronic device shown, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the electronic device of the present invention can be set in the electronic device, and the electronic device calls the lower limb assisted exoskeleton gait recognition and assisted control program stored in the memory 1005 through the processor 1001, and executes the lower limb assisted exoskeleton gait recognition and assisted control method provided in an embodiment of the present invention.

[0118] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0119] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0120] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0121] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0122] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0123] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A lower limb power-assisted exoskeleton gait recognition and power-assisted control system, characterized in that: include: A joint motion information acquisition module, used for measuring joint motion information and outputting the joint motion information to a gait phase estimation module, a joint angle position control module and a joint torque control module respectively; The gait phase estimation module is used to perform gait phase judgment according to the joint motion information to determine the current gait phase; The joint angle position control module is used to control the exoskeleton system using a joint angle position control mode when the current gait phase is in the stance phase; The joint torque control module is used to control the exoskeleton system in a joint torque control mode when the current gait phase is in the swing phase.

2. The system according to claim 1, characterized in that The joint motion information acquisition module is specifically used to measure the joint angular position, angular velocity and angular acceleration based on the inertial sensor to obtain the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal; and generate the joint motion information according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal.

3. The system according to claim 1, characterized in that The gait phase estimation module is further used to receive plantar pressure data transmitted by the plantar pressure sensor; The gait phase estimation module is specifically used to determine the gait phase according to the joint motion information to obtain an initial gait phase; The support-related joint angle threshold and the swing-related joint angle threshold are calibrated according to the plantar pressure data, and the initial gait phase determined based on the joint motion information is calibrated and aligned to determine the current gait phase.

4. The system according to claim 1, characterized in that The joint angle position control module is specifically used to use the joint angle position control mode to take the joint motion information as feedback and servo-control the exoskeleton system according to the angle position curve to generate active power support when the current gait phase is in the support phase.

5. The system according to claim 1, wherein: The joint torque control module is used to adopt the joint torque control mode to perform auxiliary torque control on the exoskeleton system according to the joint motion information combined with the human-machine dynamics model when the current gait phase is in the swing phase, so as to realize the flexible tracking control of the wearer's joints by the exoskeleton joints.

6. A method for gait recognition and power-assisted control of a lower limb power-assisted exoskeleton, characterized in that: include: Measuring joint motion information; Performing gait phase judgment according to the joint motion information to determine the current gait phase; When the current gait phase is in the stance phase, the exoskeleton system is controlled using the joint angle position control mode; When the current gait phase is in the swing phase, the joint torque control mode is adopted to control the exoskeleton system.

7. The method according to claim 6, characterized in that When the current gait phase is in the stance phase, the exoskeleton system is controlled using the joint angle position control mode, including: When the current gait phase is in the stance phase, a preset reference assisting joint angle waveform is used as a reference waveform and the joint motion information is used as feedback; generating a control signal based on a deviation between the reference waveform and the fed-back data; Based on the position servo controller, according to the control signal, the exoskeleton system is servo-controlled according to the angular position curve to generate active power support.

8. The method according to claim 7, characterized in that The joint angle position control algorithm adopted by the position servo controller is: Where τ is the output torque of the joint motor; Δθ = θ d -θ is the joint angle deviation; θ d is the expected joint angle; ΣΔθ is the historical accumulated joint angle deviation; is the joint angular velocity deviation; K p K is the proportional control gain of the joint angle controller; i K is the integral control gain of the joint angle controller; d is the differential control gain of the joint angle controller; τ ff is the feedforward torque compensation term, which is used to compensate for joint friction and damping.

9. The method according to claim 6, characterized in that When the current gait phase is in the swing phase, the exoskeleton system is controlled in a joint torque control mode, including: When the current gait phase is in the swing phase, determining a joint angle signal, a joint angular velocity signal, and a joint angular acceleration signal according to the joint motion information; Based on the human-machine dynamics model, the output torque of the joint motor is obtained according to the joint angle signal, the joint angular velocity signal and the joint angular acceleration signal; Based on the motor current loop servo control algorithm, a control signal is generated through a current loop controller according to the deviation between the torque motor current and the reference value of the current loop control loop; The exoskeleton system is subjected to auxiliary torque control based on the control signal, so as to achieve flexible tracking control of the wearer's joints by the exoskeleton joints.

10. The method according to claim 9, characterized in that The expression of the torque generator of the human-machine dynamics model is: Among them, θ is the joint angle signal; Joint angular velocity signal; Joint angular acceleration signal; H(θ) is the inertia matrix; is the Coriolis force matrix; F(θ) is the friction matrix; G(θ) is the gravity matrix; τ ω is the wearer’s torque; τ is the output torque of the joint motor; Reference current I d for: Among them, K s is the motor torque coefficient; The expression of the motor current loop servo control algorithm is: U=K Ip ΔI+K Ii ΣΔI+K Id (ΔI-ΔI a ) Where I is the torque motor current; ΔI=I d -I is the current deviation value at the current moment, ∑ΔI is the historical accumulated current deviation value, ΔI a is the current deviation value at the previous moment, K Ip is the proportional control gain of the current controller; K Ii is the current controller integral control gain, K Id is the current controller derivative control gain.

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