Force impedance dynamic flexibility control method and system for humanoid robot

Abstract

The invention discloses a force impedance dynamic flexibility control method for a humanoid robot, and relates to the technical field of robot control, and the method comprises the steps: designing a dynamic sliding mode surface as a combination of an inner ring expected contact force and a derivative of the humanoid robot; an inner ring expected contact force input control law is designed, so that the error of the inner ring expected contact force of the humanoid robot is minimum; based on a dynamic sliding mode surface and an inner ring expected contact force input control law, designing an outer ring force impedance control law by enabling a force impedance characteristic to approach a force impedance expected characteristic; the outer loop force impedance control law comprises a bearing capacity compensation parameter identification error number, and the bearing capacity compensation parameter identification error is converged to a bearing capacity compensation parameter identification error threshold value, so that the dynamic flexibility control of the force impedance of the robot is realized. The invention further discloses a force impedance dynamic flexibility control system of the humanoid robot, the dynamic flexibility of posture operation of the humanoid robot can be achieved, force impedance control precision is effectively achieved, and good multi-working-condition adaptability is achieved.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, in particular to a force impedance dynamic compliance control method and system of a humanoid robot. Background Art

[0002] In the humanoid robot force impedance double closed-loop system, the joints are equivalent to mass-spring-damper systems, where the spring stiffness coefficient, damping coefficient and mass coefficient are generally determined by the robot's automatic sensing and identification to adjust the body shape and movement gait to adapt to the specific terrain environment when it contacts different terrains. At present, the force impedance control methods for humanoid robots mainly include fuzzy logic methods, passive observer methods, parameter sensitivity analysis, compensation controllers and dynamic surface control methods.

[0003] After searching relevant patents and literature at home and abroad, regarding the force impedance control method of robots, there are papers such as "Robot Cartesian Space Force / Impedance Control Method Based on Passive Observer", which analyzes the passivity of the system and studies the stability conditions of Cartesian space force / impedance control. It is found that only the output of the force controller will destroy the passivity of the system. According to the analysis results of the passivity of the system, a force / impedance controller using a passive observer is designed. This method cannot avoid the impact force on the surrounding environment. Another paper "Design of Interactive Control System of Upper Limb Rehabilitation Robot Based on Force Impedance Model" designs a resistance strain gauge bridge circuit, processes the transmission signal, constructs a robot target impedance model, and adjusts the position, speed and joints based on the force impedance control strategy. In order to improve the singular configuration, the joint angular velocity command near the singular configuration is directly obtained by the torque damping control of each joint, realizing the precise output control of the angular velocity. However, this method is difficult to fully meet the system design in terms of telescopic joint position tracking. For example, the patent application with application number 202211004966.3 and name "Force impedance control method integrating feedforward compensation and variable damping modeling" integrates adaptive feedforward PI compensation and deep neural network variable damping model under the position impedance control framework, wherein the adaptive PI control effectively compensates for the reference position information through feedforward control and reduces the force steady-state error; the deep neural network variable damping model adjusts the damping coefficient online in real time to dynamically adapt to the unknown contact environment and realize effective control of the contact force. This method increases the control difficulty due to the high requirements on the accuracy of feedforward compensation modeling.

[0004] Although the above patent application is related to the research on the force impedance control method of humanoid robots in contact with targets, for the contact model before simplification, if the above proposed method is used to modify it, it is difficult to apply it to humanoid robots without the difficulty of mutual interference of parameter sensitivity in capturing unknown targets. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a method and system for controlling the dynamic compliance of the force impedance of a humanoid robot. The present invention reduces the parameter identification error of the transfer function from the expected contact force of the inner ring to the force impedance of the outer ring, achieves the dynamic compliance of the posture operation of the humanoid robot, effectively realizes the force impedance control accuracy and has good adaptability to multiple working conditions.

[0006] The present invention adopts the following technical solutions to solve the above technical problems:

[0007] In a first aspect, the present invention provides a method for controlling dynamic compliance of a humanoid robot by force impedance.

[0008] The dynamic sliding surface is designed to be a combination of the expected contact force and its derivatives of the inner ring of the humanoid robot;

[0009] Based on the designed dynamic sliding surface, the inner loop expected contact force input control law is designed to minimize the inner loop expected contact force error of the humanoid robot.

[0010] Based on the dynamic sliding surface and the inner ring desired contact force input control law, the outer ring force impedance control law is designed by making the force impedance characteristics approach the desired force impedance characteristics.

[0011] The outer loop force impedance control law includes the load-bearing capacity compensation parameter identification error, and the load-bearing capacity compensation parameter identification error converges to the load-bearing capacity compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

[0012] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention, the dynamic sliding surface s is designed to be a combination of the inner ring expected contact force of the humanoid robot and its derivative, including:

[0013]

[0014] Among them, F d is the expected contact force of the inner ring, is the expected contact force derivative of the inner ring, and Λ is the diagonal gain positive definite matrix.

[0015] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention,

[0016] F d =K a F r (e d -e) (2)

[0017] Among them, K a is the servo valve amplifier gain, F r is the input force, ed is the expected vector of the position and posture of the humanoid robot, and e is the vector of the robot's position and posture.

[0018] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention, the inner loop expected contact force input control law H is designed. a for

[0019]

[0020] Among them, G a is the outer loop force impedance control law, G s1 and G s2 are the first and second compensation controllers used for the outer ring force impedance, φ(s) is the transfer function from the inner ring desired contact force to the outer ring force impedance, and d(t) is the interference position.

[0021] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention, by I (s) Approaches the expected characteristics of force impedance Design the outer loop force impedance control law G a , G a as follows:

[0022]

[0023] in, for e d The second derivative, for e d First-order derivative, is the expected value of the robot inertia matrix, is the expected value of the bearing capacity matrix, Z d It is the bearing capacity compensation parameter identification error.

[0024] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention, the bearing capacity compensation parameter identification error Z d for,

[0025]

[0026] in, F d The second-order derivative of for The derivative of is the estimated value of the expected contact force of the inner ring, for The derivative of for The second derivative of d ,d and C d are the impedance matrix, load matrix and stiffness matrix of the humanoid robot shutdown module, η d , d and C d They are respectively used to adjust the dynamic compliance, impedance performance and contact stiffness of the response process between the humanoid robot and the contact target.

[0027] As a further optimization scheme of the force impedance dynamic compliance control method of a humanoid robot described in the present invention, the bearing capacity compensation parameter identification error Z d Converges to the limit value of the error in the identification of the bearing capacity compensation parameters

[0028] Among them, k1 and k2 are nonlinear coefficients.

[0029] In a second aspect, an embodiment of the present invention further provides a force impedance dynamic compliance control system for a humanoid robot, comprising:

[0030] Dynamic sliding surface design module, used to design the dynamic sliding surface as a combination of the expected contact force and its derivative of the inner ring of the humanoid robot;

[0031] The inner loop expected contact force control module is used to design the inner loop expected contact force input control law based on the designed dynamic sliding surface, so as to minimize the inner loop expected contact force error of the humanoid robot;

[0032] The outer loop force impedance control module is used to design the outer loop force impedance control law based on the dynamic sliding surface and the inner loop expected contact force input control law by making the force impedance characteristics approach the expected force impedance characteristics. The outer loop force impedance control law includes the bearing force compensation parameter identification error. The bearing force compensation parameter identification error converges to the bearing force compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

[0033] In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the processor executes the computer program, the steps of the force impedance dynamic compliance control method of a humanoid robot as described in the first aspect above or any corresponding embodiment thereof are implemented.

[0034] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the force impedance dynamic compliance control method of a humanoid robot as described in the first aspect or any corresponding embodiment thereof are implemented.

[0035] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0036] (1) Compared with the passive observer method, the force impedance control method of the dual closed-loop control system based on the outer-loop force impedance control law and the inner-loop expected contact force takes into account the strong nonlinearity, time-varying parameters and load variability of the inner loop of the expected contact force of the docking target carrier, and solves the problem of difficulty in establishing the control model caused by the dynamic change of the contact target. It will make the solution more optimized, so that the global optimal solution in the application sense can be accurately obtained.

[0037] (2) Compared with parameter sensitivity analysis, this method adopts the force impedance control method of a dual closed-loop control system consisting of an outer loop force impedance control law and an inner loop expected contact force, which reduces the parameter identification error of the transfer function from the inner loop expected contact force to the outer loop force impedance, achieves the dynamic compliance of the humanoid robot's posture operation, effectively realizes the force impedance control accuracy and has good adaptability to multiple working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of the present invention;

[0039] Figure 2 It is a comparison chart of control effects. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] This method adopts a dual closed-loop control system of outer-loop force impedance control law and inner-loop expected contact force to realize a dynamic compliance control method of force impedance of a humanoid robot. It takes into account the strong nonlinearity, time-varying parameters and load variability of the inner loop of the expected contact force of the docking target carrier, solves the problem of difficulty in establishing a control model caused by the dynamic change of the contact target, and makes the solution more optimized, so that the global optimal solution in the sense of application can be accurately obtained. The parameter identification error of the transfer function from the inner-loop expected contact force to the outer-loop force impedance is reduced, and the dynamic compliance of the posture operation of the humanoid robot is achieved, and the force impedance control accuracy is effectively realized with good adaptability to multiple working conditions.

[0042] To achieve the above objectives, the present invention is implemented through the following technical solutions: a force impedance dynamic compliance control method of a humanoid robot is implemented through a double closed-loop control system of an outer-loop force impedance control law and an inner-loop desired contact force, comprising the following steps:

[0043] like Figure 1As shown, first, the dynamic sliding surface is designed as a combination of the inner ring expected contact force of the humanoid robot and its derivative. Based on the designed dynamic sliding surface, in order to minimize the error of the inner ring expected contact force of the humanoid robot, the inner ring expected contact force input control law is designed. Based on the dynamic sliding surface and the inner ring expected contact force input control law, the outer ring force impedance control law is designed by approaching the force impedance characteristics to the expected force impedance characteristics, so as to realize the dynamic compliance of the posture operation of the humanoid robot. The outer ring force impedance control law includes the load compensation parameter identification error, and the load compensation parameter identification error converges to the load compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

[0044] When certain conditions are met, the compensation controller parameters used to trigger the outer-loop force impedance are changed from constant parameters to time-varying adaptive parameters. The triggering condition is to use the detected damping feedback value to provide a basis for the identification error of the compensation parameter. Therefore, when the humanoid robot contact sensor moves in free space, the actual damping feedback value is zero; when the contact sensor has problems such as collision, oscillation, or even instability, the damping feedback value should be non-zero. In order to prove the stability of the above outer-loop force impedance control law acting on the dynamic sliding surface, when the Lyapunov function of the humanoid robot shutdown module control system is constant negative definite, the compensation parameter identification error is more stable, indicating that the overall performance of the system has been improved throughout the control cycle. Therefore, through the dual closed-loop control system of the outer-loop force impedance control law and the inner-loop expected contact force, the control system acting on the dynamic sliding surface is asymptotically stable over a large range.

[0045] The dynamic sliding surface s is designed to be a combination of the expected contact force of the inner ring of the humanoid robot and its derivative, including:

[0046]

[0047] Among them, F d is the expected contact force of the inner ring, is the inner ring expected contact force derivative, and Λ is the diagonal gain positive definite matrix. Among them, the inner ring expected contact force can be expressed as,

[0048] F d =K a F r (e d -e) (2)

[0049] Among them, K a is the servo valve amplifier gain, F r is the input force, e d is the expected vector of the position and posture of the humanoid robot, and e is the robot position and posture vector. In order to minimize the error of the expected contact force of the inner loop of the humanoid robot, the expected contact force input control law H is designed.a for

[0050]

[0051] Among them, G a is the outer loop force impedance control law, G s1 and G s2 are the first and second compensation controllers used for the outer loop force impedance, φ(s) is the transfer function from the inner loop expected contact force to the outer loop force impedance, and d(t) is the interference position. The inner loop expected contact force input control law of the robot is related to the interference position d(t). By transforming the force impedance characteristic G I (s) Approaches the expected characteristics of force impedance Design the outer loop force impedance control law G a ,

[0052]

[0053] in, for e d The second derivative, for e d First-order derivative, is the expected value of the robot inertia matrix, is the expected value of the bearing capacity matrix, Z d It is the bearing capacity compensation parameter identification error.

[0054] In order to reduce the parameter identification error of the transfer function from the inner ring expected contact force to the outer ring force impedance and realize the dynamic compliance of the humanoid robot posture operation, the load compensation parameter identification error Z d Expanded to,

[0055]

[0056] in, F d The second-order derivative of for The derivative of is the estimated value of the expected contact force of the inner ring, for The derivative of for The second derivative of d , d and C d are the impedance matrix, load matrix and stiffness matrix of the humanoid robot shutdown module, η d , d and C d They are respectively used to adjust the dynamic compliance, impedance performance and contact stiffness of the response process between the humanoid robot and the contact target.

[0057] When the bearing capacity compensation parameter identification error Z d Converges to the limit value of the error in the identification of the bearing capacity compensation parameters The inner loop expected contact force between the humanoid robot and the contact target approaches the actual expected contact force, and the outer loop force impedance trajectory will eventually converge to the expected outer loop force impedance trajectory, thereby achieving the dynamic compliance control requirements of the robot.

[0058] Bearing capacity compensation parameter identification error Z d Converges to the limit value of the error in the identification of the bearing capacity compensation parameters

[0059] Among them, k1 and k2 are nonlinear coefficients, It is the error limit value of bearing capacity compensation parameter identification.

[0060] When the humanoid robot joint module control system meets certain conditions, the compensation controller parameters used to trigger the outer loop force impedance are changed from constant parameters to time-varying adaptive parameters. The trigger condition is to use the detected damping feedback value to provide a basis for the identification error of the compensation parameter, thereby reducing the maximum error of the control system under multiple working conditions.

[0061]

[0062] Where: is the damping feedback value, sgn(·) is the sign function. When the humanoid robot contact sensor moves in free space, the actual damping feedback value is zero. When the contact sensor has problems such as collision, oscillation or even instability, the damping feedback value should be non-zero.

[0063] In order to prove the stability of the above outer loop force impedance control law acting on the dynamic sliding surface, the Lyapunov function V(s) is defined as:

[0064]

[0065] Where ||·|| is the absolute value of the vector modulus, and the superscript T indicates transpose.

[0066] When the Lyapunov function of the humanoid robot shutdown module control system is constant negative, the compensation parameter identification error is more stable, indicating that the overall performance of the system has been improved during the entire control cycle. Therefore, the error of the humanoid robot contacting the target is minimized through the dual closed-loop control system of the outer loop force impedance control law and the inner loop expected contact force. Figure 2 As shown, the method of the present invention finds that the control system acting on the dynamic sliding surface reaches asymptotic stability most quickly at 5 seconds, and has the smallest average amplitude, compared with the traditional force impedance method.

[0067] The embodiment of the present invention further provides a force impedance dynamic compliance control system of a humanoid robot, comprising:

[0068] Dynamic sliding surface design module, used to design the dynamic sliding surface as a combination of the expected contact force and its derivative of the inner ring of the humanoid robot;

[0069] The inner loop expected contact force control module is used to design the inner loop expected contact force input control law based on the designed dynamic sliding surface, so as to minimize the inner loop expected contact force error of the humanoid robot;

[0070] The outer loop force impedance control module is used to design the outer loop force impedance control law based on the dynamic sliding surface and the inner loop expected contact force input control law by making the force impedance characteristics approach the expected force impedance characteristics. The outer loop force impedance control law includes the bearing force compensation parameter identification error. The bearing force compensation parameter identification error converges to the bearing force compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

[0071] An embodiment of the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the processor executes the computer program, the steps of the force impedance dynamic compliance control method of a humanoid robot as described in the first aspect above or any corresponding embodiment thereof are implemented.

[0072] An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the force impedance dynamic compliance control method of a humanoid robot as described in the first aspect or any corresponding embodiment thereof.

[0073] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0074] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0077] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0078] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling the dynamic compliance of a humanoid robot by force impedance, characterized in that: The dynamic sliding surface is designed to be a combination of the expected contact force and its derivatives of the inner ring of the humanoid robot; Based on the designed dynamic sliding surface, the inner loop expected contact force input control law is designed to minimize the inner loop expected contact force error of the humanoid robot. Based on the dynamic sliding surface and the inner ring desired contact force input control law, the outer ring force impedance control law is designed by making the force impedance characteristics approach the desired force impedance characteristics. The outer loop force impedance control law includes the load-bearing capacity compensation parameter identification error, and the load-bearing capacity compensation parameter identification error converges to the load-bearing capacity compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

2. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 1, characterized in that: The dynamic sliding surface s is designed to be a combination of the expected contact force of the inner ring of the humanoid robot and its derivative, including: Among them, F d is the expected contact force of the inner ring, is the expected contact force derivative of the inner ring, and Λ is the diagonal gain positive definite matrix.

3. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 2, characterized in that: F d =K a F r (e d -e)(2) Among them, K a is the servo valve amplifier gain, F r is the input force, e d is the expected vector of the position and posture of the humanoid robot, and e is the vector of the robot's position and posture.

4. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 2, characterized in that: Design the inner loop desired contact force input control law H a for Among them, G a is the outer loop force impedance control law, G s1 and G s2 are the first and second compensation controllers used for the outer ring force impedance, φ(s) is the transfer function from the inner ring desired contact force to the outer ring force impedance, and d(t) is the interference position.

5. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 4, characterized in that: By taking the force impedance characteristic G I (s) Approaches the expected characteristics of force impedance Design the outer loop force impedance control law G a , G a as follows: in, for e d The second derivative, for e d First-order derivative, is the expected value of the robot inertia matrix, is the expected value of the bearing capacity matrix, Z d It is the bearing capacity compensation parameter identification error.

6. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 5, characterized in that: Bearing capacity compensation parameter identification error Z d for, in, F d The second-order derivative of for The derivative of is the estimated value of the expected contact force of the inner ring, for The derivative of for The second derivative of d , d and C d are the impedance matrix, load matrix and stiffness matrix of the humanoid robot shutdown module, η d , d and C d They are respectively used to adjust the dynamic compliance, impedance performance and contact stiffness of the response process between the humanoid robot and the contact target.

7. The method for controlling force impedance dynamic compliance of a humanoid robot according to claim 6, characterized in that: Bearing capacity compensation parameter identification error Z d Converges to the limit value of the error in the identification of the bearing capacity compensation parameters Among them, k1 and k2 are nonlinear coefficients.

8. A force impedance dynamic compliance control system for a humanoid robot, characterized in that: include: Dynamic sliding surface design module, used to design the dynamic sliding surface as a combination of the expected contact force and its derivative of the inner ring of the humanoid robot; The inner loop expected contact force control module is used to design the inner loop expected contact force input control law based on the designed dynamic sliding surface, so as to minimize the inner loop expected contact force error of the humanoid robot; The outer loop force impedance control module is used to design the outer loop force impedance control law based on the dynamic sliding surface and the inner loop expected contact force input control law by making the force impedance characteristics approach the expected force impedance characteristics. The outer loop force impedance control law includes the bearing force compensation parameter identification error. The bearing force compensation parameter identification error converges to the bearing force compensation parameter identification error limit value, so that the error of the humanoid robot contacting the target is minimized, thereby realizing the dynamic compliance control of the robot force impedance.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the force impedance dynamic compliance control method of the humanoid robot as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the force impedance dynamic compliance control method of a humanoid robot as described in any one of claims 1 to 7 are implemented.

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