Generalized impedance exponential integral sliding mode control method and device for hexapod robot

Abstract

The present invention belongs to the technical field related to robot control, and discloses a generalized impedance exponential integral sliding mode control method and device for a hexapod robot. The method includes: establishing a spatial dynamic model of the leg joint of the hexapod robot and mapping it to Cartesian space, considering the modeling uncertainty and disturbance effects; constructing a generalized impedance model that integrates inertia, damping, rigidity and contact force tracking error weights; defining auxiliary variables based on impedance errors, designing exponential global nonlinear integral sliding mode surfaces and new convergence laws, and forming a controller. The device includes core components such as a trajectory planner, a kinematic solution module, and a control decision module, and realizes multi-module collaboration through dynamic inverse solution and a driver interface. The present invention integrates sliding mode control with an impedance model to ensure accurate tracking and control of the contact force and position of the foot end of the hexapod fire ant robot in the presence of modeling uncertainty and disturbances.

Description

Technical Field

[0001] The present invention relates to the technical field related to robot control, and more specifically, to a generalized impedance exponential integral sliding mode control method and device for a hexapod robot in a disaster environment. Background Art

[0002] In recent years, with the increasing application of mobile robots in rescue and exploration, how to make hexapod robots move stably and efficiently in disaster environments has become a key research issue in this field. The complex terrain and unpredictable interference factors in disaster environments put forward higher requirements for the precise control of the hexapod fire ant robot's foot.

[0003] However, there are still many challenges to achieve precise control of the foot contact force and position of the hexapod fire ant robot in this environment. First, the complex terrain conditions (ground with varying rigidity, rugged surfaces, etc.) require the robot to have rapid adjustment capabilities to adapt to the changing environment. Second, the foot force control needs to accurately coordinate the position while maintaining stability to prevent the hexapod robot from overturning or losing balance in disaster environments.

[0004] However, traditional control methods often find it difficult to achieve coordinated control of foot position and force under conditions of uncertainty and strong interference, and are prone to lose sight of one while focusing on another, making it impossible for the robot to achieve stable and efficient movement. Summary of the invention

[0005] The purpose of the present invention is to provide an innovative exponential integral sliding mode control method for a six-legged fire ant robot based on a generalized impedance model for disaster environments, so as to solve one or more problems raised by the above-mentioned background technology. In a disaster environment, the control method calculates the output of the controller based on the feedback of the foot end position and contact force signal of the six-legged fire ant robot, and acts on the legs of the six-legged fire ant robot, thereby realizing precise control of the foot end contact force and position. This method can realize rapid dynamic adjustment of the foot end contact force and position of the six-legged fire ant robot, and has good robustness to uncertainty and interference, thereby effectively coping with the challenges faced by the control of the precise contact force and position of the foot end of the six-legged fire ant robot in disaster environments.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A generalized impedance exponential integral sliding mode control method for a hexapod robot, the method comprising:

[0008] S1: Aiming at the disaster environment, a dynamic model of the legs of the six-legged fire ant robot in the joint space is established and mapped to the Cartesian space. In this process, the influence of modeling uncertainty and disturbance on the foot control of the six-legged fire ant robot is fully considered, and a simplified model of the environment is constructed at the same time;

[0009] S2: Aiming at the tracking control requirements of the contact force and position of the foot end of the six-legged fire ant robot in disaster environments, a generalized impedance model is introduced, which includes inertia, damping, rigidity and contact force tracking error weight coefficient;

[0010] S3: Auxiliary variables are established based on impedance error, which indirectly include the foot position, velocity, acceleration and contact force tracking error of the six-legged fire ant robot;

[0011] S4: An exponential global nonlinear integral sliding mode surface based on auxiliary variables is designed, and a new reaching law is designed to suppress chattering, thereby constructing an exponential global nonlinear integral sliding mode control framework for the six-legged fire ant robot based on the generalized impedance model. The controller output is calculated based on the tracking error between the feedback foot position and force of the six-legged fire ant robot and the expected value, thereby achieving control of the foot position and force.

[0012] Furthermore, the dynamic model including modeling uncertainty and disturbance in step S1 is as follows:

[0013]

[0014] In the formula, and They represent the velocity and acceleration vectors of the foot end of the hexapod fire ant robot in Cartesian space respectively; , For uncertainty The upper bound value of , Interference The upper bound value of , is the aggregate upper bound of uncertainty and interference terms, Represents the controller output.

[0015] Furthermore, the simplified environment model in step S1 is:

[0016]

[0017] In the formula, is the contact force vector, is the environmental rigidity coefficient matrix, and Represent the position and equilibrium position of the foot of the six-legged fire ant robot in Cartesian space, respectively. Usually replaced with the desired position This is to facilitate the tracking control of the foot end position and force of the six-legged fire ant robot when the equilibrium position changes.

[0018] Furthermore, the generalized impedance model established in step S2 is:

[0019]

[0020] In the formula, , and are the expected inertia matrix, the expected damping matrix and the expected stiffness matrix, respectively. represents the contact force tracking error weight coefficient matrix; , and They are the foot position tracking error, velocity tracking error and acceleration tracking error of the six-legged fire ant robot. The contact force tracking error of the foot end is selected according to the control requirements. The position tracking control accuracy of the foot end of the six-legged fire ant robot in Cartesian space can be improved by increasing The contact force tracking control accuracy of the foot end of the six-legged fire ant robot can be improved.

[0021] Furthermore, step S3 includes the following steps:

[0022] Step S3-1, establish the impedance error as follows:

[0023]

[0024] In the formula, is the impedance error, is the position tracking error vector of the foot end of the six-legged fire ant robot, is the velocity tracking error vector of the foot end, is the acceleration tracking error vector at the foot end, is the contact force tracking error vector at the foot end;

[0025] Step S3-2, construct auxiliary variables based on the impedance error as follows:

[0026]

[0027] In the formula, is an auxiliary variable, and is a non-singular coefficient matrix, As auxiliary items, is the derivative of the auxiliary term, and the impedance error is deformed by constructing auxiliary variables.

[0028] Furthermore, the new reaching law designed in step S4 is:

[0029]

[0030] In the formula is the weight coefficient, , increase while reducing The chattering can be suppressed.

[0031] Furthermore, the final controller form obtained in step S4 is as follows:

[0032]

[0033] In the formula, as well as are the equivalent acceleration and equivalent velocity of the foot end of the six-legged fire ant robot; Represents the controller output; represents the mass matrix, , used to describe the inertial characteristics of the hexapod robot foot in Cartesian space; represents the centrifugal force and Coriolis force matrix, , used to deal with the influence of centrifugal force and Coriolis force during robot movement; represents the gravity matrix, , reflecting the mechanical term of the robot foot end being acted upon by gravity in Cartesian space; represents the contact force, , which represents the force generated when the foot of the hexapod robot contacts the external environment.

[0034] A six-legged robot generalized impedance exponential integral sliding mode control device is used to implement a six-legged robot generalized impedance exponential integral sliding mode control method, comprising: a trajectory planner, a kinematic solution module, a control decision module, a dynamic inverse solution module, a driver interface module, a six-legged fire ant robot leg joint driver module, an actuator module and a sensor module.

[0035] Furthermore, the trajectory planner is used to plan the expected motion trajectory of a single leg of the six-legged fire ant robot in Cartesian space according to the task requirements of the six-legged fire ant robot, and the expected trajectory includes the changes of position, velocity, acceleration and contact force signals over time; the control decision module calculates the expected control force of the foot end of the six-legged fire ant robot required to achieve the expected trajectory according to the tracking error between the expected trajectory information provided by the trajectory planner and the real-time trajectory information fed back by the sensor module; the dynamics inverse solution module converts the expected control force of the foot end of the six-legged fire ant robot output by the control decision module into the corresponding joint torque; the driver interface module converts the joint torque information transmitted by the dynamics inverse solution module into a signal suitable for the six-legged fire ant robot leg joint driver module to receive; the six-legged fire ant robot leg joint driver module generates energy to drive the actuator module to move according to the signal transmitted by the driver interface module; the actuator module directly acts on the joint of the leg of the six-legged fire ant robot, and the torque generated by the motor drives the joint movement; the sensor module monitors the motion state information of the foot end of the six-legged fire ant robot in real time, and feeds this information back to the control decision module.

[0036] In general, compared with the prior art, the hexapod robot generalized impedance exponential integral sliding mode control method of the present invention has the following beneficial effects:

[0037] 1) The present invention proposes a generalized impedance exponential integral sliding mode control method for a hexapod robot, which uses a generalized impedance model including inertia, damping, rigidity and contact force tracking error weight coefficients to dynamically adjust the position and force of the foot end of the hexapod fire ant robot.

[0038] 2) The present invention takes into account the influence of modeling uncertainty and disturbance of the mechanical leg system of the six-legged fire ant robot on the tracking control performance in a disaster environment, and designs an exponential global nonlinear integral sliding mode control based on auxiliary variables to improve the robustness of the system and achieve finite time convergence of the tracking error.

[0039] 3) The generalized impedance exponential integral sliding mode control method for the hexapod robot proposed in the present invention designs a new type of exponential global nonlinear integral sliding mode control. Through the compensation term, the state trajectory of the system is globally in the sliding mode stage to avoid the integral saturation phenomenon. The exponential term is designed to achieve finite time convergence of the tracking error and can achieve rapid dynamic adjustment in the entire control process.

[0040] 4) The present invention has a simple structure, is easy to implement in practical applications, has good robustness to system modeling uncertainty and disturbance, and has a relatively precise control effect on the foot end position and force of the six-legged fire ant robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings of the present invention are used to provide a further understanding of the embodiments of the present invention, constitute a part of this specification, and exemplarily illustrate the embodiments of the present invention and the description thereof, and are used to explain the principles of the present invention.

[0042] Figure 1 A control block diagram of a generalized impedance exponential integral sliding mode control method for a hexapod robot according to an exemplary embodiment of the present invention;

[0043] Figure 2 Schematic diagram of the position tracking effect in the x-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0044] Figure 3 Schematic diagram of the speed tracking effect in the x-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0045] Figure 4 Schematic diagram of the position tracking effect in the y-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0046] Figure 5 Schematic diagram of the speed tracking effect in the y-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0047] Figure 6 Schematic diagram of the position tracking effect in the z-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0048] Figure 7 Schematic diagram of the speed tracking effect in the z-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0049] Figure 8 Schematic diagram of the contact force tracking effect in the z-axis direction under the generalized impedance exponential integral sliding mode control method of the hexapod robot;

[0050] Fig. 9 A flow chart showing a generalized impedance exponential integral sliding mode control method for a hexapod robot according to an exemplary embodiment of the present invention;

[0051] Fig.10 It is a structural schematic diagram of the generalized impedance exponential integral sliding mode control device of the hexapod robot of the present invention;

[0052] Fig.11 It is a schematic diagram of the electronic device structure of the generalized impedance exponential integral sliding mode control of the hexapod robot of the present invention. DETAILED DESCRIPTION

[0053] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments of the present invention, and it should be understood that the present invention is not limited by the exemplary embodiments described herein. It should be noted that unless otherwise specifically stated, the relative arrangement of the components and steps, the numerical expressions and the numerical values ​​described in these embodiments do not limit the scope of the present invention. It can be understood by those skilled in the art that the terms "first", "second", "S1", "S2" and the like in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor represent the necessary logical order between them. It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more. It should also be understood that for any component, data or structure mentioned in the embodiments of the present invention, in the absence of explicit limitation or contrary revelation given in the context, it can generally be understood as one or more. In addition, the term "and / or" in the present invention is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the objects associated with each other are in an "or" relationship. It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects can be referenced to each other. For the sake of brevity, they will not be described one by one. The following description of at least one exemplary embodiment is actually only illustrative and is by no means a limitation on the present invention and its application or use. Technologies, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the technologies, methods and equipment should be considered as part of the specification.

[0054] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc. Terminal devices, computer systems, servers, etc. Electronic devices can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, target programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0055] Exemplary Methods

[0056] Figure 1 The control block diagram of a generalized impedance exponential integral sliding mode control method for a six-legged robot for disaster environments is schematically shown, taking the six-legged fire ant robot as the research object.

[0057] In this embodiment, the mechanical legs (i.e., legs) of the six-legged fire ant robot have three rotation joints. To solve the problem of tracking the contact force and position of the foot end of the six-legged fire ant robot in a disaster environment, Figures 1 to 8 As shown, the generalized impedance exponential integral sliding mode control method of the hexapod robot includes the following steps:

[0058] S1: Establish the dynamic model of the legs of the six-legged fire ant robot in the joint space and map it to the Cartesian space. In this process, fully consider the impact of modeling uncertainty and disturbance on control performance and construct a simplified model of the environment;

[0059] S2: Establish a generalized impedance model, select appropriate inertia, damping, rigidity and contact force tracking error weight coefficients, obtain the corrected desired trajectory, and adjust the model coefficients according to the actual force and position control requirements;

[0060] S3: Establish impedance error. On the basis of impedance error, construct auxiliary variables including foot position tracking error, velocity tracking error and contact force tracking error of the six-legged fire ant robot, and use them as intermediate control variables of the generalized impedance model to deform the impedance error.

[0061] S4: The constructed auxiliary variables are embedded into the exponential global nonlinear integral sliding surface, and a new reaching law is designed to suppress the chattering to obtain the final controller. In the presence of modeling uncertainty and disturbance, the tracking error between the position, velocity and contact force obtained from the foot-end feedback of the six-legged fire ant robot and the expected value is calculated to obtain the controller output, and act on the leg to achieve the control of the contact force and position of the foot-end of the six-legged fire ant robot.

[0062] This method can be used to achieve coordinated control of precise force and position of the foot of the six-legged fire ant robot in a disaster environment. A generalized impedance model including inertia coefficient, damping coefficient, stiffness coefficient and contact force tracking error weight coefficient is used to realize the dynamic adjustment of the contact force and position of the foot during the continuous movement of the six-legged fire ant robot. Auxiliary variables based on impedance error are designed to achieve coordinated control of contact force and position. At the same time, in order to solve the influence of uncertainty and interference on control performance, a new exponential global nonlinear integral sliding surface based on auxiliary variables is designed, thereby constructing an exponential global nonlinear integral sliding control framework for the six-legged fire ant robot based on the generalized impedance model. Through the compensation term in the exponential global nonlinear integral sliding surface, the control effect of the six-legged fire ant robot is effectively controlled. The design makes the state trajectory of the system globally in the sliding mode stage, so as to avoid the integral saturation phenomenon. The finite time convergence of the tracking error is achieved by designing the exponential term in the exponential global nonlinear integral sliding surface, and fast dynamic adjustment can be achieved in the entire control process. In addition, the design combines a new approach law of the softsign function to suppress the chattering phenomenon and further improve the tracking control performance of the system. Finally, the efficient and stable motion of the six-legged fire ant robot is achieved in a disaster environment with uncertainty and strong interference.

[0063] The specific plan is as follows:

[0064] The step S1: for the disaster environment, a dynamic model of the legs of the six-legged fire ant robot in the joint space is established, and it is mapped to the Cartesian space. In this process, the influence of modeling uncertainty and disturbance on the control performance is fully considered, and a simplified model of the environment is constructed, which specifically includes:

[0065] Step S1-1, considering that the six-legged fire ant robot has three rotation joints in its legs, the mechanical leg dynamics model in the joint space is established as follows:

[0066]

[0067] in, represents the joint torque of the mechanical leg, represents the joint angle vector, is the joint angular velocity vector, represents the joint angular acceleration vector, represents the mass matrix, represents the centrifugal force and Coriolis force matrix, represents the gravity matrix, represents the inverse of the transposed Jacobian matrix, Represents the contact force (also referred to as force for short).

[0068] Step S1-2, transform the dynamic model into Cartesian space and consider the modeling uncertainty δ and the disturbance term d:

[0069]

[0070] and They represent the velocity and acceleration vectors of the foot of the six-legged fire ant robot in Cartesian space, is the Cartesian space mass matrix, is the centrifugal force and Coriolis force matrix in Cartesian space, is the Cartesian space gravity matrix, represents the contact force, , For uncertainty The upper bound value of , Interference The upper bound value of , is the aggregate upper bound of uncertainty and interference terms, Represents the controller output.

[0071] in, and They represent the velocity and acceleration vectors of the foot end of the hexapod fire ant robot in Cartesian space respectively; , For uncertainty The upper bound value of , Interference The upper bound value of , For uncertainty and distractors The lumped upper bound value of ; represents the controller output, represents the Cartesian space mass matrix, represents the position of the foot of the six-legged fire ant robot in Cartesian space, is the centrifugal force and Coriolis force matrix in Cartesian space, is the Cartesian space gravity matrix.

[0072] Step S1-3: Establish a simplified model of the environment ,in, is the contact force vector, is the environmental rigidity coefficient matrix, represents the equilibrium position of the foot of the six-legged fire ant robot in Cartesian space, but Usually replaced with the desired position , so as to realize the tracking control of the foot end position and force of the six-legged fire ant robot when the equilibrium position changes.

[0073] The step S2: in response to the tracking and control requirements of the contact force and position of the foot end of the six-legged fire ant robot in a disaster environment, a generalized impedance model including an inertia coefficient, a damping coefficient, a stiffness coefficient and a contact force tracking error weight coefficient is preset, so as to establish a dynamic relationship between the foot end position and the contact force of the six-legged fire ant robot, and realize dynamic adjustment of the foot end position and force of the six-legged fire ant robot.

[0074] The generalized impedance model established in step S2 is:

[0075] in, , and are the expected inertia matrix, the expected damping matrix and the expected stiffness matrix, respectively. represents the contact force tracking error weight coefficient matrix, is the position tracking error vector of the foot end of the six-legged fire ant robot, is the velocity tracking error vector of the foot end of the six-legged fire ant robot, is the acceleration tracking error vector of the foot end of the six-legged fire ant robot, is the contact force tracking error vector of the foot end of the six-legged fire ant robot. The coefficient is reasonably selected according to the control requirements. By increasing Kd, the position tracking control accuracy of the foot end of the six-legged fire ant robot in Cartesian space can be improved, and by increasing Kf, the contact force tracking control accuracy of the foot end of the six-legged fire ant robot can be improved.

[0076] The step S3: establishing impedance error, on this basis constructing an auxiliary variable z that indirectly includes the foot position tracking error, velocity tracking error, acceleration tracking error and contact force tracking error of the six-legged fire ant robot, and using it as an intermediate control quantity of the generalized impedance model to achieve coordinated control of force and position, specifically including:

[0077] Step S3-1, establishing impedance error for:

[0078] in, is the impedance error;

[0079] Step S3-2, based on the impedance error The auxiliary variable z is constructed by the foot position tracking error, velocity tracking error and contact force tracking error of the six-legged fire ant robot as follows:

[0080]

[0081] in, is an auxiliary variable, and is a non-singular coefficient matrix, As auxiliary items, is the derivative of the auxiliary term;

[0082] By constructing the auxiliary variable z to calculate the impedance error To transform.

[0083] S4: Design an exponential global nonlinear integral sliding surface based on auxiliary variables, embed the constructed auxiliary variable z into the exponential global nonlinear integral sliding surface, and design a new reaching law to suppress chattering, and obtain the final controller. The controller output is obtained according to the tracking error between the feedback foot end position and contact force of the six-legged fire ant robot and the expected value, thereby realizing the control of the foot end contact force and position of the six-legged fire ant robot, specifically including:

[0084] Step S4-1: construct an exponential global nonlinear integral sliding surface s based on the auxiliary variable z:

[0085] in, , is the index term, and is the exponential adjustment coefficient, λ=z(0) is the auxiliary variable The initial value of , a, b and r are positive coefficients, and t represents time;

[0086] The auxiliary variable z is used as the tracking control variable to achieve the tracking control of the foot end position and force of the six-legged fire ant robot.

[0087] In this way, an exponential global nonlinear integral sliding mode control framework for the six-legged fire ant robot based on the generalized impedance model was constructed. As a compensation term, the state trajectory of the system is globally in the sliding mode stage to avoid integral saturation. As an exponential term, it achieves finite-time convergence of the tracking error and enables dynamic regulation throughout the control process.

[0088] Step S4-2: Design the reaching law as follows:

[0089]

[0090] in, is the weight coefficient, represents the derivative of the sliding surface, s represents the sliding surface, , sign(s) represents the sign function, For uncertainty and distractors The lumped upper bound value of ;

[0091] Increase while reducing The chattering can be suppressed.

[0092] Step S4-3: The final controller form is as follows:

[0093]

[0094] In the formula, as well as are the equivalent acceleration and equivalent velocity of the foot end of the six-legged fire ant robot; Represents the controller output; represents the mass matrix, , used to describe the inertial characteristics of the hexapod robot foot in Cartesian space; represents the centrifugal force and Coriolis force matrix, , used to deal with the influence of centrifugal force and Coriolis force during robot movement; represents the gravity matrix, , reflecting the mechanical term of the robot foot end being acted upon by gravity in Cartesian space; represents the contact force, , which represents the force generated when the foot of the hexapod robot contacts the external environment.

[0095] Therefore, an exponential global nonlinear integral sliding mode control framework of the hexapod fire ant robot based on the generalized impedance model is constructed. According to the feedback information of the foot position and contact force of the hexapod fire ant robot, the mechanical leg control input required to track the expected position and the expected contact force is calculated by the above formula, that is, the controller output is calculated according to the tracking error between the feedback foot position and force of the hexapod fire ant robot and the expected value, so as to realize the tracking control of the contact force and position of the foot of the hexapod fire ant robot in the presence of modeling uncertainty δ and disturbance d.

[0096] The step S4 uses the designed auxiliary variable z as the tracking control quantity, embeds it into the exponential global nonlinear integral sliding surface s, realizes the finite time convergence of the tracking error, and can avoid the integral saturation phenomenon while enhancing the system robustness. At the same time, a new reaching law is designed to suppress the chattering phenomenon.

[0097] like Figure 2-Figure 8 As shown, in order to solve the problem of tracking the contact force and position of the foot end of the six-legged fire ant robot in a disaster environment, under the control method of the present invention, the foot end of the six-legged fire ant robot achieves accurate and rapid trajectory tracking in the x-axis, y-axis and z-axis directions, and at the same time, the contact force of the foot end of the six-legged fire ant robot in the z-axis direction is also accurately tracked and controlled.

[0098] Exemplary Devices

[0099] Fig.10 It is a structural schematic diagram of a generalized impedance exponential integral sliding mode control device for a six-legged robot provided by an exemplary embodiment of the present invention. This embodiment includes: a trajectory planner, a kinematic solution module, a control decision module, a dynamic inverse solution module, a driver interface module, a six-legged fire ant robot leg joint driver module, an actuator module and a sensor module.

[0100] The trajectory planner is used to plan the expected motion trajectory of a single leg of the hexapod fire ant robot in Cartesian space according to the task requirements of the hexapod fire ant robot (such as walking and crossing obstacles). The expected trajectory includes the changes of position, velocity, acceleration and contact force signals over time.

[0101] The control decision module (an exponential integral sliding mode control method for a hexapod robot including a generalized impedance model) calculates the expected control force at the foot end of the hexapod fire ant robot required to achieve the expected trajectory based on the tracking error between the expected trajectory information (position, velocity, acceleration and contact force) provided by the trajectory planner and the real-time trajectory information (position, velocity, acceleration and contact force) fed back by the sensor module.

[0102] The dynamic inverse solution module converts the desired control force at the foot end of the six-legged fire ant robot output by the control decision module into the corresponding joint torque.

[0103] The driver interface module converts the joint torque information transmitted by the dynamic inverse solution module into a signal (such as a PWM signal) suitable for the leg joint driver module of the six-legged fire ant robot to receive.

[0104] The leg joint driver module of the six-legged fire ant robot generates energy (such as appropriate voltage / current signal) to drive the actuator module to move according to the signal transmitted from the driver interface module.

[0105] The actuator module directly acts on the joints of the legs of the six-legged fire ant robot, and the torque generated by the motor drives the joint movement.

[0106] The sensor module monitors the motion state information (position, velocity, acceleration and contact force) of the foot of the six-legged fire ant robot in real time, and feeds this information back to the control decision module.

[0107] Exemplary Electronic Devices

[0108] Fig.11 This is the structure of an electronic device 80 provided by an exemplary embodiment of the present invention. The electronic device can be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device can communicate with the first device and the second device to receive the collected input signals from them. Figure 8 FIG. 1 is a block diagram of an electronic device according to an embodiment of the present disclosure. Figure 8 As shown, the electronic device includes one or more processors 81 and a memory 82 .

[0109] The processor 81 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0110] The memory 82 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 81 may run the program instructions to implement the CNN-based flight target position prediction method and / or other desired functions of the software program of each embodiment of the present disclosure described above. In one example, the electronic device may also include: an input device 83 and an output device 84, which are interconnected through a bus system and / or other forms of connection mechanisms (not shown). In addition, the input device 83 may also include, for example, a keyboard, a mouse, etc. The output device 84 may output various information to the outside. The output device 84 may include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, etc.

[0111] Of course, to simplify, Fig.11Only some of the components related to the present disclosure in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device may further include any other appropriate components.

[0112] Exemplary computer program products and computer-readable storage media

[0113] In addition to the above-mentioned methods and devices, an embodiment of the present disclosure may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section of this specification.

[0114] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0115] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above “Exemplary Method” section of this specification.

[0116] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0117] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0118] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0119] The block diagrams of the devices, apparatuses, equipment, and systems involved in this disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including," "comprising," "having," and the like are open words, referring to "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or," and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0120] The method and apparatus of the present disclosure may be implemented in many ways. For example, the method and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0121] It should also be noted that in the apparatus, equipment and method of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present disclosure. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present disclosure. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown here, but to the widest scope consistent with the principles and novel features disclosed herein.

[0122] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A generalized impedance exponential integral sliding mode control method for a hexapod robot, characterized in that: The method comprises the following steps: S1: Establish the dynamic model of the hexapod robot's legs in the joint space, map it to the Cartesian space, consider the influence of modeling uncertainty and disturbance on the hexapod fire ant robot's foot control, and construct a simplified model of the environment; S2: A generalized impedance model including inertia coefficient, damping coefficient, stiffness coefficient and contact force tracking error weight coefficient is established for the hexapod robot; S3: Based on the generalized impedance model, the impedance error is obtained. On the basis of the impedance error, an auxiliary variable z is constructed, which includes the foot position tracking error, velocity tracking error and contact force tracking error of the six-legged fire ant robot. It is used as the intermediate control quantity of the generalized impedance model to adjust the impedance error. Transformation is performed, where: in, is an auxiliary variable, , and is a non-singular coefficient matrix, is the position tracking error vector of the foot end of the six-legged fire ant robot, is the velocity tracking error vector of the foot end of the six-legged fire ant robot, For auxiliary items, is the derivative of the auxiliary term; S4: Construct an exponential global nonlinear integral sliding surface, and embed the constructed auxiliary variables into the exponential global nonlinear integral sliding surface s: in, , is the index term, and is the exponential adjustment coefficient, λ=z(0) is the auxiliary variable The initial value of , a, b and r are positive coefficients, t represents time, and the auxiliary variable z is used as the tracking control quantity to achieve tracking control of the foot end position and force of the six-legged fire ant robot.

2. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 1, characterized in that: The generalized impedance model established for the hexapod robot in step S2 is: In the formula, , and are the expected inertia matrix, the expected damping matrix and the expected stiffness matrix, respectively. represents the contact force tracking error weight coefficient matrix, , , and They are acceleration tracking error vector, velocity tracking error vector, position tracking error vector and contact force tracking error vector respectively.

3. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 2, characterized in that: The impedance error established in step S3 is as follows: In the formula, is the impedance error.

4. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 3, characterized in that: The step S4 comprises the following steps: Step S4-2: Design the reaching law as follows: in, is the weight coefficient, represents the derivative of the sliding surface, s represents the sliding surface, , sign(s) represents the sign function, , For uncertainty The upper bound value of , Interference The upper bound value of , is the aggregate upper bound of uncertainty and interference terms, by increasing while reducing uncertainty and distractors The aggregate upper bound of , thereby achieving the suppression of chattering.

5. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 4, characterized in that: The step S4 comprises the following steps: S4-3: Build the final controller : In the formula, as well as are the equivalent acceleration and equivalent velocity of the foot end of the six-legged fire ant robot; Represents the controller output; represents the mass matrix, , used to describe the inertial characteristics of the hexapod robot foot in Cartesian space; represents the centrifugal force and Coriolis force matrix, , used to deal with the influence of centrifugal force and Coriolis force during robot movement; represents the gravity matrix, , reflecting the mechanical term of the robot foot end being acted upon by gravity in Cartesian space; represents the contact force, , which represents the force generated when the foot of the hexapod robot contacts the external environment.

6. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 5, characterized in that: The foot position of the six-legged fire ant robot based on feedback and contact force The controller output is calculated And act on the legs of the hexapod robot, thereby achieving precise control of the contact force and position of the foot end.

7. The hexapod robot generalized impedance exponential integral sliding mode control method according to claim 1, characterized in that: The hexapod robot is a six-legged fire ant robot with three rotating joints in its legs. The dynamic model of the mechanical legs in the joint space is established as follows: in, represents the joint torque of the mechanical leg, represents the joint angle vector, is the joint angular velocity vector, represents the joint angular acceleration vector, represents the mass matrix, represents the centrifugal force and Coriolis force matrix, represents the gravity matrix, represents the inverse of the transposed Jacobian matrix, represents the contact force; Step S1-2, transform the dynamic model into Cartesian space and take into account the modeling uncertainty and distractors : in, and They represent the velocity and acceleration vectors of the foot of the six-legged fire ant robot in Cartesian space, is the Cartesian space mass matrix, is the centrifugal force and Coriolis force matrix in Cartesian space, is the Cartesian space gravity matrix, represents the contact force, To model uncertainty, is a disturbance term, and , For uncertainty and distractors The lumped upper bound value, Represents the controller output; Step S1-3: Establish a simplified environmental model as follows: In the formula, is the contact force vector, is the environmental rigidity coefficient matrix, and Represent the position and equilibrium position of the foot of the six-legged fire ant robot in Cartesian space, respectively. Usually replaced with the desired position This is to facilitate tracking control of the foot end position and contact force of the six-legged fire ant robot when the equilibrium position changes.

8. A hexapod robot generalized impedance exponential integral sliding mode control device, used to implement the hexapod robot generalized impedance exponential integral sliding mode control method according to any one of claims 1 to 7, characterized in that: include: Trajectory planner, kinematics solution module, control decision module, dynamics inverse solution module, driver interface module, six-legged fire ant robot leg joint driver module, actuator module and sensor module.

9. A hexapod robot generalized impedance exponential integral sliding mode control device according to claim 8, characterized in that: The trajectory planner is used to plan the expected motion trajectory of a single leg of the six-legged fire ant robot in Cartesian space according to the task requirements of the six-legged fire ant robot, and the expected trajectory includes the changes of position, velocity, acceleration and contact force signals over time; the control decision module calculates the expected control force of the foot end of the six-legged fire ant robot required to achieve the expected trajectory according to the tracking error between the expected trajectory information provided by the trajectory planner and the real-time trajectory information fed back by the sensor module; the dynamics inverse solution module converts the expected control force of the foot end of the six-legged fire ant robot output by the control decision module into the corresponding joint torque; the driver interface module converts the joint torque information transmitted by the dynamics inverse solution module into a signal suitable for the six-legged fire ant robot leg joint driver module to receive; the six-legged fire ant robot leg joint driver module generates energy to drive the actuator module to move according to the signal transmitted by the driver interface module; the actuator module directly acts on the joint of the leg of the six-legged fire ant robot, and the torque generated by the motor drives the joint movement; the sensor module monitors the motion state information of the foot end of the six-legged fire ant robot in real time, and feeds this information back to the control decision module.

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