Tensioning integral robot rolling motion method based on closed-loop control

Abstract

The invention discloses a tensegrity robot rolling motion method, system and device based on closed-loop control, and belongs to the technical field of robot motion. The method comprises the following steps: selecting a rolling shaft and a driving point based on a minimum direction principle according to a target point position of rolling of the tensegrity robot; according to the rolling shaft and the driving point, planning a motion track of a rolling angle and a rolling radius of the tensegrity robot, and calculating a mass center motion expected track based on the planned motion track of the rolling angle and the rolling radius of the tensegrity robot; the tensegrity robot dynamical model considering the contact collision condition is used for tracking the mass center motion expected track of the tensegrity robot, and a mass center motion expected instruction is obtained. According to the method, the problems that in the rolling process, the structural deformation of the whole tensioning robot is large, the motion performance is limited, and the rolling efficiency is low are solved, and the rolling speed of the tensioning robot is accurately controlled.

Description

Technical Field

[0001] The present invention relates to the field of robot motion technology, and in particular to a rolling motion method, system and equipment of a tensegrity robot based on closed-loop control. Background Art

[0002] When exploring unknown areas, responding to emergency disasters, and performing high-risk tasks, robotics technology has become an indispensable helper for humans with its unique advantages. Among them, Tensegrity Robots, as an emerging form of robots, have shown great application potential in many fields such as planetary exploration, post-disaster emergency rescue, and special environment exploration due to their unique structural characteristics and excellent performance indicators. The design concept of tensegrity robots is derived from an ancient structural philosophy - through the clever combination of tensile elements and compression elements, a stable and flexible overall structure is formed. This structure not only has an extremely high strength-to-weight ratio, can maintain the stability and integrity of the structure in extreme environments, but also can adapt to complex and changing terrains and environments due to its unique deformation ability.

[0003] However, it is precisely this structural complexity that brings unprecedented challenges to the rolling motion control of tensegrity robots. Compared with traditional wheeled, tracked or legged robots, the movement of tensegrity robots is more unique and complex. It mainly rolls around its rolling axis in contact with the ground. This rolling method not only requires the robot to be able to flexibly adjust its shape to adapt to different rolling requirements, but also requires precise control of the synergy of various components to ensure the smoothness and efficiency of the rolling process.

[0004] At present, the research community has proposed two main strategies for the rolling motion control technology of tensegrity robots: open-loop control method and intelligent control method. The open-loop control method is usually based on a preset algorithm or model, and moves the center of mass position of the tensegrity robot to the outside of the rolling axis by changing the shape of the tensegrity robot, thereby achieving single-step rolling motion. This method has the advantages of simple implementation and small amount of calculation, but due to the lack of real-time feedback on the external environment and in-depth consideration of structural dynamics, its rolling efficiency and stability are often limited. In practical applications, the open-loop control method is difficult to cope with complex and changeable rolling environments, such as uneven terrain, changing friction coefficients, etc. These factors may lead to instability or even failure of the rolling process.

[0005] In contrast, intelligent control methods attempt to improve the adaptability and robustness of rolling motion by introducing advanced artificial intelligence technologies such as machine learning and neural networks. These methods can perceive environmental changes in real time and dynamically adjust control strategies based on the perceived information, thus overcoming the limitations of open-loop control methods to a certain extent. However, intelligent control methods also face many difficulties in implementation. First, the dynamic model of the tensegrity robot is complex and highly nonlinear, making it difficult to establish an accurate mathematical model. Second, the training and optimization of intelligent algorithms require a large amount of experimental data and computing resources, which poses a challenge to rapid response and real-time control in practical applications. Therefore, although intelligent control methods can improve the adaptability and robustness of rolling motion, they ignore the unique motion analysis problems of tensegrity robots, but do not fundamentally solve the deformation problem of the tensegrity structure during rolling, which still limits the improvement of its rolling efficiency and motion performance. Summary of the invention

[0006] The control methods existing in the prior art ignore the unique motion analysis problems of tensegrity robots, which make full use of the motion deformation ability of the tensegrity structure, resulting in large structural deformation of the tensegrity robot during its rolling process, limited motion performance, low rolling efficiency, and inability to accurately control the rolling speed of the robot. The present invention provides a tensegrity robot rolling motion method based on closed-loop control, which is based on the tensegrity robot dynamics model under contact and collision conditions, fully considers the influence of robot dynamics and contact and collision dynamics, and realizes the tensegrity robot rolling motion with controllable motion state, strong robustness, and high efficiency and continuity, solves the problems of large structural deformation, limited motion performance, and low rolling efficiency of the tensegrity robot during its rolling process, and realizes accurate control of the rolling speed of the tensegrity robot.

[0007] In order to achieve the above object, the present invention provides the following technical solutions.

[0008] In a first aspect, the present invention provides a rolling motion method of a tensegrity robot based on closed-loop control, comprising: According to the target point position of the tensegrity robot rolling, the rolling axis and driving point are selected based on the minimum direction principle; According to the rolling axis and the driving point, a motion trajectory of the rolling angle and the rolling radius of the tensegrity robot is planned, and an expected trajectory of the center of mass motion is calculated based on the planned motion trajectory of the rolling angle and the rolling radius of the tensegrity robot; By using the dynamic model of the tensegrity robot considering the contact and collision conditions, the expected trajectory of the center of mass motion of the tensegrity robot is tracked to obtain the expected center of mass motion instruction; according to the expected center of mass motion instruction, the tensegrity robot is controlled to realize the expected rolling motion with the expected rolling radius and rolling angle; When the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law of the tensegrity robot in the rolling falling stage is designed based on the partial feedback linearization control method to control the tensegrity robot to land. It is determined whether the tensegrity robot reaches the set target point when landing. If it reaches the target point, it is determined that the tensegrity robot has successfully completed the continuous rolling task.

[0009] As a further improvement of the present invention, the rolling axis and the driving point are selected based on the minimum direction principle according to the target point position of the tensegrity robot rolling, including: According to the target point position of the tensegrity robot rolling, based on the minimum direction principle, the angle between the rolling direction of the tensegrity robot and the expected direction is calculated, and the base of the ground contact triangle around which the robot completes the single-step rolling process corresponding to the minimum angle is selected as the rolling axis of the tensegrity robot in the single-step rolling process; The nodes on the opposite side of the rolling axis of the tensegrity robot in single-step rolling are selected as driving points.

[0010] As a further improvement of the present invention, the method of planning the motion trajectory of the rolling angle and the rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculating the expected trajectory of the center of mass motion based on the planned motion trajectory of the rolling angle and the rolling radius of the tensegrity robot, comprises: Plan the rolling angular motion trajectory of the tensegrity robot in the initial rolling phase according to the rolling axis and driving point and rolling radius trajectory ; Rolling angle motion trajectory of the tensegrity robot in the initial rolling stage and rolling radius trajectory , which is converted into the expected motion trajectory of the robot's center of mass ; in, is the rolling angular displacement of the robot’s center of mass at time k; is the rolling radius of the robot at time k; for; for.

[0011] As a further improvement of the present invention, a tensegrity robot dynamics model considering contact and collision conditions is used to track the expected trajectory of the center of mass motion of the tensegrity robot to obtain an expected center of mass motion instruction; and the tensegrity robot is controlled to achieve an expected rolling motion with an expected rolling radius and rolling angle according to the expected center of mass motion instruction, including: The tensegrity robot dynamics model considering contact and collision conditions is used to design the mass center trajectory tracking control law of the tensegrity robot in the initial rolling stage based on the neural network adaptive sliding mode closed-loop control method, and the expected mass center motion trajectory of the tensegrity robot is tracked to obtain the expected mass center motion instructions; The tensegrity robot is controlled to achieve a desired rolling motion with a desired rolling radius and rolling angle according to the desired center of mass motion instruction.

[0012] As a further improvement of the present invention, the method for designing the center of mass trajectory tracking control law of the tensegrity robot in the initial rolling stage based on the neural network adaptive sliding mode closed-loop control method includes:

[0013] In the formula, is the control input; The prestressed cable member balances the tension and satisfies the prestressed balance condition. ; represents the expected trajectory of the center of mass motion; , is the control law parameter matrix; for The estimated value of .

[0014] As a further improvement of the present invention, when the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law for the rolling falling stage of the tensegrity robot is designed based on a partial feedback linearization control method to control the tensegrity robot to land, including: When the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law of the tensegrity robot rolling falling stage is designed based on the partial feedback linearization control method, including the closed-loop control law of the tensegrity robot landing shock absorption control in the rolling falling stage and the closed-loop control law of the tensegrity robot landing shock absorption control in the rolling falling stage; The closed-loop control law of the tensegrity robot's landing shock absorption control during the rolling falling stage is used to control the tensegrity robot's landing shock absorption control during the rolling falling stage; The closed-loop control law of the shock absorption control of the tensegrity robot during its rolling fall phase is used to control the configuration recovery and stability control of the tensegrity robot during its rolling fall phase.

[0015] As a further improvement of the present invention, the closed-loop control law of the landing shock absorption control of the tensegrity robot during the rolling falling stage includes:

[0016] in, represents the expected vertical displacement of the robot's landing contact point, is a positive definite matrix representing the desired damping matrix, is a positive definite matrix representing the expected stiffness matrix; The closed-loop control law for the landing shock absorption control of the tensegrity robot during the rolling falling stage includes:

[0017] in, represents the expected length of the cable member, is a positive definite matrix representing the desired damping matrix, is a positive definite matrix representing the expected stiffness matrix.

[0018] As a further improvement of the present invention, the step of determining whether the tensegrity robot reaches a set target point when landing includes: Determine whether there are three nodes of the tensegrity robot in contact with the ground at the same time when it lands; If there are no three nodes that are in contact with the ground at the same time, continue to execute; If there are three nodes that are in contact with the ground at the same time, determine whether the target point is within the triangle formed by the three nodes on the bottom surface; If the target point is within the triangle, it is determined that the tensegrity robot has successfully completed a rolling motion; If the target point position is not within the triangle, the rolling axis and driving point are reselected based on the minimum direction principle according to the target point position of the tensegrity robot rolling, and the rolling motion is continued.

[0019] In a second aspect, the present invention provides a tensegrity robot rolling motion system based on closed-loop control, comprising: Roll axis and drive point selection module: used to select the roll axis and drive point based on the minimum direction principle according to the target point position of the tensegrity robot roll; A module for obtaining the expected trajectory of the center of mass movement: used for planning the trajectory of the rolling angle and the rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculating the expected trajectory of the center of mass movement based on the planned trajectory of the rolling angle and the rolling radius of the tensegrity robot; The expected rolling motion module is used to track the expected trajectory of the center of mass motion of the tensegrity robot by using the tensegrity robot dynamics model considering the contact and collision conditions, and obtain the expected center of mass motion instruction; according to the expected center of mass motion instruction, the tensegrity robot is controlled to achieve the expected rolling motion with the expected rolling radius and rolling angle; Robot landing module: when the tensegrity robot in the desired rolling motion rolls into the falling stage, the closed-loop control law of the tensegrity robot rolling and falling stage is designed based on the partial feedback linearization control method to control the tensegrity robot to land; Rolling completion judgment module: used to judge whether the tensegrity robot reaches the set target point when landing. If it reaches the target point, it is determined that the tensegrity robot has successfully completed the continuous rolling task.

[0020] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of a rolling motion method of a tensegrity robot based on closed-loop control when executing the computer program.

[0021] In a fourth aspect, the present invention 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 optical fiber line package defect detection and type identification method based on deep learning are implemented.

[0022] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the optical fiber line package defect detection and type identification method based on deep learning.

[0023] Compared with the prior art, the present invention has the following beneficial effects: The core of the present invention is to achieve refined management and optimization of the rolling process of the tensegrity robot by introducing a closed-loop control system for the unique motion analysis problem of the tensegrity robot. Traditional control methods often ignore the unique motion deformation ability of the tensegrity structure, resulting in large structural deformation of the robot during the rolling process, which not only limits its motion performance, but also reduces the rolling efficiency, and it is difficult to achieve accurate control of the rolling speed. The present invention cleverly utilizes the characteristics of the tensegrity structure, and selects the rolling axis and driving point based on the minimum direction principle to ensure the optimal selection of the rolling path, effectively reduce unnecessary structural deformation, and improve motion efficiency. On this basis, the present invention further plans the motion trajectory of the rolling angle and rolling radius of the tensegrity robot, and calculates the expected trajectory of the center of mass motion based on this planning. This step not only provides a theoretical basis for subsequent precise control, but also ensures that the robot can maintain a stable posture during the rolling process, avoiding motion instability caused by structural deformation. More importantly, the present invention introduces a tensegrity robot dynamics model that considers contact and collision conditions. This model fully considers the contact and collision of the robot with the ground or other obstacles during the rolling process, and simulates and calculates the dynamic parameters more accurately. Through this model, the present invention can track and adjust the robot's center of mass motion trajectory in real time to ensure that it always moves along the desired trajectory during the rolling process. This tracking control method based on the dynamic model not only improves the accuracy of control, but also significantly enhances the robustness of the robot, so that it can maintain a stable rolling state in a complex and changeable environment. In the falling stage of the rolling process, the present invention adopts a partial feedback linearization control method to design a closed-loop control law. This method realizes the precise control of key parameters such as landing speed and angle by real-time monitoring and analysis of the dynamic characteristics of the robot during the landing process. This not only ensures that the robot can land in a stable posture, but also further improves the continuity and stability of its rolling motion. In addition, by judging whether the robot reaches the set target point when it lands, the present invention can also accurately evaluate the success of the rolling task, providing strong data support for subsequent rolling path planning and control strategy adjustment. Therefore, the present invention realizes the comprehensive optimization and precise control of the rolling motion of the tensegrity robot by introducing a closed-loop control system, optimizing the rolling path selection, introducing a dynamic model considering contact and collision conditions, and adopting a partial feedback linearization control method. This method not only significantly reduces the structural deformation of the robot during rolling, improves its motion performance and rolling efficiency, but also achieves precise control of the rolling speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are for illustrative purposes only and are not intended to limit the scope of the present disclosure in any way. In the drawings: Figure 1A schematic flow chart of a rolling motion method of a tensegrity robot based on closed-loop control according to the present invention; Figure 2 It is a specific flow chart of the continuous rolling motion control method of the tensegrity robot of the present invention; Figure 3 A schematic diagram of the rolling axis selection of the tensegrity robot of the present invention; Figure 4 A schematic diagram showing the definition of the rolling angle and rolling radius of the tensegrity robot of the present invention; Figure 5 Schematic diagram of the forward displacement tracking curve of the center of mass of the tensegrity robot in the initial rolling stage in Example 1 of the present invention; Figure 6 It is a schematic diagram of the lateral displacement tracking curve of the center of mass of the tensegrity in the initial rolling stage in Example 1 of the present invention; Figure 7 It is a schematic diagram of a tracking curve of the vertical displacement of the center of mass of the tensegrity robot in the initial rolling stage in Example 1 of the present invention; Figure 8 A three-dimensional simulation result diagram of the initial moment of the rolling motion of the tensegrity robot in Example 1 of the present invention; Fig. 9 A three-dimensional simulation result diagram of the tensegrity robot at the end of the initial rolling stage in Example 1 of the present invention; Fig.10 A three-dimensional simulation result diagram of the tensegrity robot at the highest rolling point in Example 1 of the present invention; Fig.11 A three-dimensional simulation result diagram of the tensegrity robot in Example 1 of the present invention at the stable landing moment; Fig.12 This is a simulation diagram of the continuous rolling center of mass motion trajectory of the tensegrity robot in Example 2 of the present invention; Fig.13 It is a structural schematic diagram of a rolling motion system of a tensegrity robot based on closed-loop control according to the present invention; Fig.14 Schematic diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. The described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0027] The control methods in the prior art ignore the unique motion analysis problems of tensegrity robots, which make full use of the motion deformation ability of the tensegrity structure, resulting in large structural deformation of the tensegrity robot during rolling, limited motion performance, low rolling efficiency, and inability to accurately control the rolling speed of the robot. The present invention provides a tensegrity robot rolling motion method based on closed-loop control, such as Figure 1 As shown, the method includes: S100: According to the target point position of the tensegrity robot rolling, the rolling axis and the driving point are selected based on the minimum direction principle; S200: planning a motion trajectory of a rolling angle and a rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculating an expected trajectory of the center of mass motion based on the planned motion trajectory of the rolling angle and the rolling radius of the tensegrity robot; S300: using a tensegrity robot dynamics model taking into account contact and collision conditions, tracking a desired trajectory of the center of mass movement of the tensegrity robot, and obtaining a desired center of mass movement instruction; controlling the tensegrity robot to achieve a desired rolling movement with a desired rolling radius and rolling angle according to the desired center of mass movement instruction; S400: When the tensegrity robot in the desired rolling motion rolls into a falling phase, a closed-loop control law for the rolling falling phase of the tensegrity robot is designed based on a partial feedback linearization control method to control the tensegrity robot to land; S500: Determine whether the tensegrity robot reaches the set target point when landing, and if so, determine that the tensegrity robot has successfully completed the continuous rolling task.

[0028] This method is based on the dynamic model of the tensegrity robot under contact and collision conditions, and fully considers the influence of the robot dynamics and contact and collision dynamics, to achieve a tensegrity robot rolling motion with controllable motion state, strong robustness, and efficient continuity, to solve the problems of large structural deformation, limited motion performance, and low rolling efficiency of the tensegrity robot during the rolling process, and to achieve precise control of the rolling speed of the tensegrity robot.

[0029] The present invention is further explained below in conjunction with the specific drawings.

[0030] The present invention provides a rolling motion method of a tensegrity robot based on closed-loop control. The method is based on the dynamic model of the tensegrity robot under contact and collision conditions, fully considering the influence of robot dynamics and contact and collision dynamics, and realizes the rolling motion of the tensegrity robot with controllable motion state, strong robustness, and high efficiency and continuity. The method flow chart is as follows: Figure 2 As shown, the specific steps are as follows: S1: Based on the minimum direction principle and the position of the tensegrity robot's rolling target point, the robot's rolling axis and driving point in single-step rolling are selected, including: The rolling axis is defined as the base of the ground contact triangle around which the robot completes a single-step rolling process. Figure 3 The schematic diagram of the tensegrity robot touching the ground is shown in the figure. represents the tensegrity robot's ground contact triangle, is the center of mass of the robot The projection in The scroll target point. , , Perpendicular to of , , The three sides are the rolling directions of the robot, with each side as the rolling axis. , , The scroll direction and the desired direction The robot can quickly approach the target point by selecting the bottom side corresponding to the smallest angle as the rolling axis and the node on the opposite side of the rolling axis as the driving point.

[0031] S2: Based on the quadratic programming method, the motion trajectory of the rolling angle and rolling radius of the tensegrity robot in the initial rolling stage is planned, and then the expected trajectory of the center of mass motion is calculated through the expected trajectory of the rolling angle and rolling radius.

[0032] The motion trajectory of the rolling angle and rolling radius of the tensegrity robot in the initial rolling stage is planned based on the quadratic programming method, and then the expected trajectory of the center of mass motion is calculated through the expected trajectory of the rolling angle and rolling radius.

[0033] Based on the closed-loop control method, this application proposes a rolling motion strategy for a tensegrity robot, which decomposes the rolling motion process of the tensegrity robot into the initial rolling stage (from the initial state to the moment when its driving point leaves the ground) and the rolling drop stage (from the moment when the driving point leaves the ground to the robot stabilizing on the ground). In the initial rolling stage, the driving point provides the torque required for the robot to complete rolling around the rolling axis; in the rolling drop stage, the driving point leaves the ground, and the motion process can be simplified to the simple pendulum motion of the center of mass around the rolling axis.

[0034] like Figure 4 As shown in the figure The tensegrity robot touches the ground triangle. Taking edge scrolling as an example, define The side is the rolling axis, Provide the driving point with the torque required for the robot to complete rolling. is the robot's center of mass, for exist The projection in for A little satisfaction on the side , for and The angle between is defined as the rolling angle, for The length of is defined as the rolling radius. In the initial stage of rolling, the process of the robot's center of mass moving around the rolling axis can be described as the change process of the rolling angle and rolling radius. Through the trajectory planning method, the robot enters the simple pendulum motion of the rolling falling stage at the end of the initial stage of rolling (when the driving point leaves the ground) with the desired rolling angle, rolling angular velocity, and rolling radius, so that the robot can complete a rolling motion around the rolling axis.

[0035] S2.1: Plan the rolling angular motion trajectory of the tensegrity robot during the initial rolling phase.

[0036] The roll angle motion of the tensegrity robot can be expressed by the following linear model: (1) In the formula, represents the roll angle motion vector, is the rolling angular displacement of the robot's center of mass at time k, , , , Represents the simulation step size.

[0037] The expected initial stage time of robot rolling is specified as Based on formula (1), the rolling angle motion prediction model of the robot in the initial rolling stage can be obtained as: (2) Where: is the expected rolling angle trajectory of the robot in the initial rolling stage; is the solution of the quadratic programming; for; for.

[0038] The rolling angle motion trajectory is planned through the following quadratic programming problem: (3) In the formula, is the weight matrix, represents the expected rolling angular displacement at the end of the initial rolling phase, represents the expected rolling angular velocity at the end of the initial rolling phase, Indicates the expected rolling radius at the end of the initial rolling phase. To ensure that the center of mass can cross the rolling axis to complete the rolling during the rolling drop phase, the expected angular velocity at the end The following relationship needs to be satisfied: (4) The solution of the quadratic programming Substituting into formula (2), we can get the expected rolling angle trajectory of the robot in the initial rolling stage: .

[0039] S2.2: Planning the rolling radius change trajectory of the tensegrity robot in the initial rolling stage The robot rolling radius trajectory planning process is the same as the rolling angle planning method. The linear model and prediction model of the robot rolling radius can be expressed as: (5) (6) In the formula, , is the rolling radius of the robot at time k, , , .

[0040] The rolling radius trajectory is planned through the following quadratic programming problem: (7) In the formula, is the weight matrix, is the forward acceleration of the center of mass, is the vertical acceleration of the center of mass, which can be expressed as: (8) The solution of the quadratic programming Substituting into formula (6), we can get the rolling radius trajectory of the robot in the initial stage of rolling: .

[0041] S2.3: Convert the expected rolling angle trajectory and the expected rolling radius trajectory into the expected motion trajectory of the robot's center of mass.

[0042] Roll angle trajectory of the tensegrity robot and rolling radius trajectory , the center of mass motion trajectory in the initial stage of rolling can be expressed as: (9) in, is the forward motion trajectory in the initial stage of rolling; It is the vertical motion trajectory in the initial stage of rolling.

[0043] By taking the first-order derivative and the second-order derivative of formula (9), we can obtain the velocity trajectory and acceleration trajectory of the center of mass motion in the initial stage of the robot's rolling.

[0044] S3: Based on the neural network adaptive sliding mode closed-loop control method, the center of mass trajectory tracking control law of the tensegrity robot in the initial rolling stage is designed to realize the robot's center of mass motion trajectory tracking to control the robot to achieve the desired rolling motion.

[0045] A dynamic model of the tensegrity robot in the form of ordinary differential equations for control law design is established, and the center of mass trajectory tracking control law of the tensegrity robot in the initial rolling stage is designed based on the neural network adaptive sliding mode closed-loop control method. The expected center of mass motion instructions obtained in the tracking trajectory planning are used to control the robot to achieve the desired rolling motion with the desired rolling radius and rolling angle.

[0046] In order to design the closed-loop control law of the tensegrity robot, it is first necessary to establish the dynamic model of the tensegrity robot considering the contact and collision conditions, and convert it into the form of ordinary differential equations for control law design. Then, the closed-loop control law design is performed based on the ordinary differential equations. The specific steps are as follows: S3.1: Establish a dynamic model of the tensegrity robot considering contact and collision conditions, and transform it into an ordinary differential equation for control law design. Specifically, it includes: The dynamic model of the tensegrity robot considering contact and collision conditions can be expressed as follows: (10) In the formula, represents the generalized coordinate vector of the tensegrity robot, indicating the position and orientation of the robot rod components; represents the inertia matrix; ; represents the tensegrity structure equilibrium matrix, The elements can be expressed as , Indicates the length of the cable member; represents the manipulation matrix, , , , is the Young's modulus of the cable member, Represents the cross-sectional area of ​​the cable member. represents the control input, Indicates the original length of the cable member; represents the normal contact generalized force vector between the robot node and the environment surface, represents the tangential friction generalized force vector between the robot node and the environment surface, For the complete constraints of the generalized coordinates of the tensegrity robot rod components, is the corresponding Lagrange multiplier; , is the normal distance between the robot’s ith node and the environment surface, is the embedding depth of the robot's ith node along the normal direction of the environment surface; is the normal contact force of the ith node of the robot.

[0047] The contact and collision complementary relationship of the tensegrity robot described by the last two terms in formula (10) can be equivalently expressed as: (11) In the formula, the set Represents a set of nodes that have no contact with the environment surface. Represents the collection of nodes that are in contact with the environment surface.

[0048] Substituting formula (11) into formula (10), the dynamic model of the tensegrity robot can be expressed as: (12) In the formula, , represents the normal support force of the environment contact node, represents the tangential friction force of the environment contact node; , represents the normal distance of the contact node relative to the environment surface, represents the tangential displacement of the contact node; , The Jacobian matrix representing the robot's constraint space.

[0049] Jacobian matrix of the constraint space The null space The projection operator can be expressed as , then its orthogonal complement space The projection operator can be expressed as .

[0050] Multiply the differential equation in formula (12) by get: (13) Taking the first-order derivative of the equality constraint in formula (12) yields: (14) The generalized velocity components of the system can be expressed as: (15) Taking the derivative of formula (15) we can get (16) In the formula, .

[0051] Adding equation (13) to equation (16) yields the tensegrity robot dynamics equation in the form of an ordinary differential equation for control law design: (17) In the formula, , , .

[0052] S3.2: Design the center of mass trajectory tracking control law for the initial rolling stage of the tensegrity robot based on the neural network adaptive sliding mode closed-loop control method, and track the desired center of mass motion instructions obtained in trajectory planning to control the robot to achieve the desired rolling motion with the desired rolling radius and rolling angle.

[0053] The control goal of the tensegrity robot in the initial stage of rolling is to control the robot's center of mass to track the desired trajectory. The robot's center of mass is selected as the task space: (18) In the formula, represents the centroid position vector, Represents the Jacobian matrix of the robot task space.

[0054] Multiply formula (17) by Substituting into formula (18), the robot center of mass task space dynamics can be expressed as: (19) In the formula, , , Uncertainty It can be approximated by RBF neural network, and formula (19) can be expressed as: (20) In the formula, is the ideal weight matrix of the neural network, is the neural network approximation error vector, is the radial basis function vector, the vector Each element in is selected as a Gaussian function: (twenty one) In the formula, is the input of the neural network, represents the center vector, Represents the width of the Gaussian function.

[0055] In order to ensure the stability of the closed-loop system, the sliding surface is designed to represent the ideal closed-loop system dynamic characteristics as follows: (twenty two) In the formula, is the tracking error, is a positive definite matrix.

[0056] By deriving formula (22) and substituting it into formula (20), the sliding mode dynamics of the system can be expressed as: (twenty three) Design the robot neural network adaptive sliding mode closed-loop control law as: (twenty four) In the formula, Input for prestress balance control of tensegrity structures; is the robot motion torque instruction; Indicates the prestressed balanced tension of the cable member, satisfying the prestressed balance condition ; represents the expected trajectory of the center of mass motion; , is the control law parameter matrix; for The estimated value of is, and its adaptive law is: (25) In the formula, are control law parameters.

[0057] The boundary layer method is used in formula (24) to reduce the system chattering caused by sliding mode control, and the saturation function is used to replace the original discontinuous term: (26) In the formula, Represents the boundary layer thickness.

[0058] Substituting formula (24) into formula (23), the sliding mode dynamics of the closed-loop system can be expressed as: (27) In the formula, .

[0059] Furthermore, the stability analysis of the proposed controller is carried out and the Lyapunov function is defined as follows: (28) In the formula, , .

[0060] Formula (28) satisfies the following inequality relationship: (29) In the formula, , .

[0061] Taking the derivative of formula (28) and substituting it into formula (27) yields: (30) because is a constant matrix, there exists make The neural network estimation error satisfies .when When , formula (30) can be further simplified as: (31) Pick ,when , When , formula (31) can be further simplified as: (32) In the formula, .

[0063] According to the Lyapunov function inequality relationship shown in formula (29) and formula (32), it can be proved that Eventually uniformly bounded. Sliding mode dynamics Being able to converge to the boundary layer ensures that the closed-loop system error vector It can also be constrained to be a linear function of its boundary layer thickness.

[0064] S4: Design a closed-loop control law for the rolling descent phase of the tensegrity robot based on the partial feedback linearization control method to control the robot to maintain a balanced configuration and land smoothly.

[0065] Based on the partial feedback linearization control method, a closed-loop control law for the rolling falling stage of the tensegrity robot is designed to control the robot to achieve landing shock absorption to ensure that it can land smoothly and recover and maintain a balanced configuration after landing, including: S4.1: Shock absorption control of the tensegrity robot during rolling fall During the robot rolling and falling stage, the ground contact force is regarded as an external disturbance. Based on the linear projection operator method in S3, the dynamic model of the tensegrity robot shown in formula (10) can be simplified as follows: (33) In the formula, , , , , , .

[0066] In order to ensure that the tensegrity robot can land smoothly during the rolling fall stage, the vertical displacement of the robot's landing contact point is selected as the task space: , (34) In the formula, represents the vertical displacement of the robot's landing contact point, Represents the Jacobian matrix of the robot task space.

[0067] Multiply formula (33) by Substituting into formula (34), the task space dynamics of the robot during the rolling and falling phase can be expressed as: (35) In the formula, , , .

[0068] Design the robot closed-loop control law as: (36) In the formula, represents the expected vertical displacement of the robot's landing contact point, is a positive definite matrix representing the desired damping matrix, is a positive definite matrix representing the expected stiffness matrix.

[0069] Substituting formula (36) into formula (35), the task space closed-loop system can be expressed as: (37) By adjusting the desired damping matrix and stiffness matrix in formula (37), the robot can achieve landing shock absorption during the rolling fall phase to ensure that it can land smoothly.

[0070] S4.2: Configuration recovery control of a tensegrity robot during rolling drop After the robot achieves rolling motion and lands smoothly, it is necessary to control the length of the robot's cable components to restore the robot to its initial configuration so that it can perform subsequent ground motion tasks.

[0071] Select the length of the tensegrity robot cable member as the task space: , (38) In the formula, represents the cable member length vector, Represents the Jacobian matrix of the robot task space.

[0072] Multiply formula (33) by Substituting into formula (38), the task space dynamics of the robot during the rolling and falling phase can be expressed as: (39) In the formula, , , .

[0073] Design the robot closed-loop control law as: (40) In the formula, represents the expected length of the cable member, is a positive definite matrix representing the desired damping matrix, is a positive definite matrix representing the expected stiffness matrix.

[0074] Substituting formula (40) into formula (39), the task space closed-loop system can be expressed as: (41) By selecting When the length of the cable component is the initial equilibrium configuration, the robot configuration can be restored to stable control during the rolling and falling phase.

[0075] S5: Determine whether there are three nodes of the tensegrity robot in contact with the ground at the same time, and determine whether the robot reaches the target point.

[0076] Determine whether there are three nodes of the tensegrity robot that are in contact with the ground at the same time; If not, continue to execute the robot rolling and falling stage control task; If so, determine whether the target point position is within the bottom triangle. If so, determine that the tensegrity robot has successfully completed a continuous rolling task; if not, return to S1 and select the rolling axis and driving point for the next rolling to continue to perform the continuous rolling task.

[0077] The present invention proposes a rolling motion method of a tensegrity robot based on closed-loop control, decomposes the robot rolling motion into the rolling initial stage and the rolling falling stage, and realizes the rolling motion of the tensegrity robot with controllable motion state, strong robustness, continuous and efficient. Secondly, the present invention provides an expected trajectory of the center of mass motion of a tensegrity robot in single-step rolling based on the quadratic programming method, describes the motion process of the robot's center of mass rolling around the rolling axis as the change process of the rolling angle and the rolling radius, and designs the expected trajectory of the center of mass motion of the robot in the initial stage of rolling that meets the expected constraints based on the quadratic programming method. Furthermore, the present invention proposes a neural network adaptive sliding mode control method to solve the problem of tracking the center of mass trajectory of a tensegrity robot under contact and collision conditions. The adaptive law of the radial basis function neural network is used to approximate the uncertainty term, and the robust tracking of the robot's center of mass trajectory is realized. Finally, the present invention proposes a shock-absorbing control method for the rolling landing of a tensegrity robot. The control law of the rolling falling stage of the tensegrity robot is designed based on the partial feedback linearization control method. By adding a damping term to the dynamics of the vertical motion task space at the robot's landing contact point, it is ensured that the robot can land smoothly in the rolling falling stage, so as to realize efficient and continuous robot rolling motion.

[0078] In summary, the present invention designs a continuous rolling motion strategy for a tensegrity robot based on a closed-loop control method, improves the rolling motion efficiency of the tensegrity robot, and realizes continuous and efficient ground rolling motion of the tensegrity robot. At the same time, based on the quadratic programming method, a desired trajectory of the center of mass motion of a tensegrity robot in single-step rolling is provided, and the motion process of the center of mass of the robot rolling around the rolling axis is described as the change process of the rolling angle and the rolling radius. In the process of the center of mass realizing rolling motion along the trajectory, the rolling torque is provided by the driving point, and the rolling motion of the robot can be realized under the premise of small structural deformation, thereby improving the rolling motion efficiency. In addition, the present invention designs a closed-loop center of mass motion trajectory tracking control law in the initial stage of the rolling of the tensegrity robot based on the neural network adaptive sliding mode control method, and compensates for the uncertainty by the neural network adaptive law, so as to realize the robust tracking of the robot center of mass motion to the expected trajectory, thereby realizing the controllable rolling of the tensegrity robot. Finally, the present invention designs a closed-loop control law in the rolling and falling stage of the tensegrity robot based on the partial feedback linearization control method, so that the robot can restore and maintain a stable configuration, and realizes the rolling landing shock absorption of the tensegrity robot, ensuring that it can land smoothly for continuous rolling.

[0079] The present invention is further explained below in conjunction with specific embodiments.

[0080] Example 1: Simulation of single-step rolling motion control of a six-rod spherical tensegrity robot The following takes the rolling motion control simulation results of a six-rod spherical tensegrity robot as an example to illustrate the effectiveness of the implementation scheme. The six-rod spherical tensegrity robot consists of 6 rod components and 24 cable components. Its specific structure is as follows: Figure 8 shown.

[0081] The simulation process parameters were set as follows: the total simulation time was 2 s, the simulation step was 0.005 s, and the initial state of the tensegrity robot was stationary on the horizontal ground.

[0082] The physical parameters of the robot and the environment are as follows: The length of the rod component is , the quality is ; The Young's modulus of the cable member is , the cross-sectional area is ; The coefficient of friction of the ground is , the acceleration due to gravity .

[0083] The parameters related to the robot's center of mass motion trajectory planning are defined as follows: , , , , , , , , , .

[0084] The relevant parameters of the tensegrity robot control law are: , , , , The initial value of is 0. , , , .

[0085] Under the above settings, the simulation results are as follows Figure 5~Figure 11 shown.

[0086] Figure 5~Figure 7 The center of mass trajectory tracking curve of the tensegrity robot in the initial rolling stage (0~0.2s), the dotted line is the expected motion trajectory of the center of mass obtained by trajectory planning, and the solid line is the actual motion trajectory of the center of mass. The simulation results show that in the initial rolling stage, the forward displacement, vertical displacement, and lateral displacement of the robot's center of mass can quickly and stably track its expected instructions, and the tracking error is kept in a small range, so that the robot can complete the initial rolling stage with the expected rolling angular velocity and rolling radius, and finally complete the expected rolling motion.

[0087] Figure 8~Figure 11This is a 3D motion state simulation diagram of the rolling motion process of the tensegrity robot. Figure 8 for Simulation result diagram at time (initial time), the tensegrity robot is stationary on the horizontal ground; Fig. 9 for The simulation result diagram at time t (the end time of the initial rolling stage), the tensegrity robot completes the center of mass trajectory tracking task in the initial rolling stage, the driving point C leaves the ground, and the robot enters the rolling falling stage. Fig.10 for The simulation result diagram at the moment (the highest point of rolling) shows that the center of mass of the robot moves to the top of its rolling axis. After this moment, the robot completes the rolling and falling stage under the action of gravity torque. Fig.11 for The simulation result diagram at moment 1 (stable landing moment) shows that the robot completes the rolling task and finally stabilizes on the horizontal ground. Under the action of the closed-loop control law in the rolling and falling stage, the robot achieves landing shock absorption, quickly stabilizes on the ground, and is able to restore and maintain the initial balanced configuration.

[0088] In summary, the closed-loop control method for the rolling motion of the tensegrity robot designed in the present invention can track the motion trajectory of the robot's center of mass in the initial stage of rolling, thereby controlling the robot to roll at a desired rolling angle and rolling radius, and can achieve rapid and smooth landing in the rolling falling stage. During the entire rolling motion process, the deformation of the tensegrity robot is kept within a small range, thereby realizing the rolling motion of the tensegrity robot with controllable motion state and high rolling efficiency, which has guiding significance for the design of the tensegrity robot motion control system.

[0089] Example 2: Simulation of continuous rolling motion control of a six-rod spherical tensegrity robot The simulation results of continuous rolling motion control of a six-rod spherical tensegrity robot illustrate the effectiveness of the control strategy proposed in this paper.

[0090] The physical parameters related to the robot and the environment, the parameters related to the trajectory planning of the robot's center of mass motion, and the parameters related to the control law of the tensegrity robot are the same as those in Example 1.

[0091] The simulation process parameters are set as follows: the total simulation time is 7.5s, the simulation step is 0.005s, the initial state of the tensegrity robot is stationary on the horizontal ground, and the initial center of mass position is , the rolling target point position is .

[0092] Under the above settings, the center of mass position of the tensegrity robot changes during continuous rolling as follows: Fig.12As shown in the figure, the gray triangle represents the motion trajectory of the ground contact triangle of the tensegrity robot during continuous rolling, the black dot represents the horizontal position of the robot's center of mass during continuous rolling, the * dot represents the horizontal position of the rolling target point, and the dotted line represents the horizontal displacement of the robot's center of mass during continuous rolling. In order to quickly approach the target point, the robot rolled five times in a row, and the rolling axis selected for each rolling shortened the distance between the robot and the target point. During the rolling process, the change process of its ground contact triangle is as follows: ( Indicates that the ground contact triangle is an equilateral triangle. Indicates that the ground contact triangle is an isosceles triangle). Through the center of mass trajectory planning and trajectory tracking control in the initial stage of rolling, the robot can be controlled to complete the rolling motion along the rolling edges of various types of ground contact triangles. After the fifth rolling, the target point position enters the robot ground contact triangle, and the robot completes a continuous rolling task, and its center of mass reaches the vicinity of the rolling target point position.

[0093] In summary, the closed-loop control method for rolling motion of a tensegrity robot designed in the present invention can realize continuous rolling motion of a tensegrity robot with controllable motion state and strong robustness.

[0094] The second object of the present invention is to provide a tensegrity robot rolling motion system based on closed-loop control, such as Fig.13 As shown, including: The rolling axis and driving point selection module 101 is used to select the rolling axis and driving point based on the minimum direction principle according to the target point position of the tensegrity robot rolling; Obtaining the expected trajectory of the center of mass movement module 201: used to plan the movement trajectory of the rolling angle and the rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculate the expected trajectory of the center of mass movement based on the planned movement trajectory of the rolling angle and the rolling radius of the tensegrity robot; The desired rolling motion module 301 is used to track the desired trajectory of the center of mass motion of the tensegrity robot by using the tensegrity robot dynamics model considering the contact and collision conditions, and obtain the desired center of mass motion instruction; and control the tensegrity robot to achieve the desired rolling motion with the desired rolling radius and rolling angle according to the desired center of mass motion instruction; Robot landing module 401: when the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law of the tensegrity robot rolling and falling stage is designed based on a partial feedback linearization control method to control the tensegrity robot to land; The module 501 for judging the completion of rolling is used to judge whether the tensegrity robot reaches the set target point when landing. If it reaches the target point, it is determined that the tensegrity robot has successfully completed the continuous rolling task.

[0095] like Fig.14 As shown, the third object of the present invention is to provide an electronic device, the electronic device comprising: a processor 601, a memory 602 and a display screen 603. Among them, the memory 602 and the display screen 603 are connected to the processor 601, such as through a bus 604. Optionally, the electronic device may also include a transceiver 605. It should be noted that in actual applications, the transceiver 605 is not limited to one, and the structure of the electronic device does not constitute a limitation on the embodiments of the present application.

[0096] Processor 601 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 601 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0097] The bus 604 may include a path to transmit information between the above components. The bus 604 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 604 may be divided into an address bus, a data bus, a control bus, etc.

[0098] The memory 602 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0099] The memory 602 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 601. The processor 601 is used to execute the application code stored in the memory 602 to implement the content shown in the above method embodiment.

[0100] Fig.14 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0101] The fourth object of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program is stored thereon, and when the program is executed by a processor, the aforementioned Figure 1 to Figure 2 The various processes of the method embodiment shown in the figure include, for example, a memory including instructions, and the instructions can be executed by a processor of an electronic device to complete the method.

[0102] A computer-readable storage medium may be a tangible device that holds and stores instructions used by an instruction execution device. A computer-readable storage medium may be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, a computer-readable storage medium may be a portable computer disk, a hard disk, a USB flash drive, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a lectern random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, an optical disk, a magnetic disk, a mechanical encoding device, and any combination thereof.

[0103] A fifth object of the present invention is to provide a computer program product, comprising computer instructions, which, when executed by a processor, implement the above Figure 1 to Figure 2 The various processes of the method embodiment shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0104] Many embodiments and many applications beyond the examples provided will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of the present teachings should not be determined with reference to the above description, but rather with reference to the preceding claims and the full scope of equivalents to which such claims are entitled. For the purpose of comprehensiveness, all articles and references, including disclosures of patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended to be a disclaimer of such subject matter, nor should it be considered that the applicants did not consider such subject matter to be part of the disclosed inventive subject matter.

[0105] The above content is a further detailed description of the present invention. It cannot be determined that the specific implementation methods of the present invention are limited to these. For ordinary technicians in the technical field to which the present invention belongs, without departing from the concept of the present invention, they can also make several simple deductions or substitutions, which should be regarded as belonging to the protection scope of the present invention determined by the submitted claims.

Claims

1. A rolling motion method of a tensegrity robot based on closed-loop control, characterized in that: include: According to the target point position of the tensegrity robot rolling, the rolling axis and driving point are selected based on the minimum direction principle; According to the rolling axis and the driving point, a motion trajectory of the rolling angle and the rolling radius of the tensegrity robot is planned, and an expected trajectory of the center of mass motion is calculated based on the planned motion trajectory of the rolling angle and the rolling radius of the tensegrity robot; By using the dynamic model of the tensegrity robot considering the contact and collision conditions, the expected trajectory of the center of mass motion of the tensegrity robot is tracked to obtain the expected center of mass motion instruction; according to the expected center of mass motion instruction, the tensegrity robot is controlled to realize the expected rolling motion with the expected rolling radius and rolling angle; When the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law of the tensegrity robot in the rolling falling stage is designed based on the partial feedback linearization control method to control the tensegrity robot to land. It is determined whether the tensegrity robot reaches the set target point when landing. If it reaches the target point, it is determined that the tensegrity robot has successfully completed the continuous rolling task.

2. A rolling motion method of a tensegrity robot based on closed-loop control according to claim 1, characterized in that: The method of selecting the rolling axis and the driving point based on the minimum direction principle according to the target point position of the tensegrity robot rolling includes: According to the target point position of the tensegrity robot rolling, based on the minimum direction principle, the angle between the rolling direction of the tensegrity robot and the expected direction is calculated, and the base of the ground contact triangle around which the robot completes the single-step rolling process corresponding to the minimum angle is selected as the rolling axis of the tensegrity robot in the single-step rolling process; The nodes on the opposite side of the rolling axis of the tensegrity robot in single-step rolling are selected as driving points.

3. The rolling motion method of a tensegrity robot based on closed-loop control according to claim 1, characterized in that: The method of planning the motion trajectory of the rolling angle and the rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculating the expected trajectory of the center of mass motion based on the planned motion trajectory of the rolling angle and the rolling radius of the tensegrity robot, comprises: Plan the rolling angular motion trajectory of the tensegrity robot in the initial rolling phase according to the rolling axis and driving point and rolling radius trajectory ; Rolling angle motion trajectory of the tensegrity robot in the initial rolling stage and rolling radius trajectory , which is converted into the expected motion trajectory of the robot's center of mass ; in, is the rolling angular displacement of the robot’s center of mass at time k; is the rolling radius of the robot at time k; for; for.

4. The rolling motion method of a tensegrity robot based on closed-loop control according to claim 1, characterized in that: By using a tensegrity robot dynamics model considering contact and collision conditions, an expected trajectory of the center of mass motion of the tensegrity robot is tracked to obtain an expected center of mass motion instruction; and according to the expected center of mass motion instruction, the tensegrity robot is controlled to achieve an expected rolling motion with an expected rolling radius and rolling angle, including: The tensegrity robot dynamics model considering contact and collision conditions is used to design the mass center trajectory tracking control law of the tensegrity robot in the initial rolling stage based on the neural network adaptive sliding mode closed-loop control method, and the expected mass center motion trajectory of the tensegrity robot is tracked to obtain the expected mass center motion instructions; The tensegrity robot is controlled to achieve a desired rolling motion with a desired rolling radius and rolling angle according to the desired center of mass motion instruction.

5. A rolling motion method of a tensegrity robot based on closed-loop control according to claim 4, characterized in that: The method for designing the center of mass trajectory tracking control law of the tensegrity robot in the initial rolling stage based on the neural network adaptive sliding mode closed-loop control method includes: In the formula, is the control input; The prestressed cable member balances the tension and satisfies the prestressed balance condition. ; represents the expected trajectory of the center of mass motion; , is the control law parameter matrix; for The estimated value of .

6. The rolling motion method of a tensegrity robot based on closed-loop control according to claim 1, characterized in that: When the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law for the rolling falling stage of the tensegrity robot is designed based on a partial feedback linearization control method to control the tensegrity robot to land, including: When the tensegrity robot in the desired rolling motion rolls into the falling stage, a closed-loop control law of the tensegrity robot rolling falling stage is designed based on the partial feedback linearization control method, including the closed-loop control law of the tensegrity robot landing shock absorption control in the rolling falling stage and the closed-loop control law of the tensegrity robot landing shock absorption control in the rolling falling stage; The closed-loop control law of the tensegrity robot's landing shock absorption control during the rolling falling stage is used to control the tensegrity robot's landing shock absorption control during the rolling falling stage; The closed-loop control law of the shock absorption control of the tensegrity robot during its rolling fall phase is used to control the configuration recovery and stability control of the tensegrity robot during its rolling fall phase.

7. A method for rolling motion of a tensegrity robot based on closed-loop control according to claim 6, characterized in that: The closed-loop control law for the landing shock absorption control of the tensegrity robot during the rolling falling stage includes: in, represents the expected vertical displacement of the robot's landing contact point, is a positive definite matrix representing the expected damping matrix, is a positive definite matrix representing the expected stiffness matrix; The closed-loop control law for the landing shock absorption control of the tensegrity robot during the rolling falling stage includes: in, represents the expected length of the cable member, is a positive definite matrix representing the expected damping matrix, is a positive definite matrix representing the expected stiffness matrix.

8. The rolling motion method of a tensegrity robot based on closed-loop control according to claim 1, characterized in that: The determining whether the tensegrity robot reaches a set target point when landing includes: Determine whether there are three nodes of the tensegrity robot in contact with the ground at the same time when it lands; If there are no three nodes that are in contact with the ground at the same time, continue to execute; If there are three nodes that are in contact with the ground at the same time, determine whether the target point is within the triangle formed by the three nodes on the bottom surface; If the target point is within the triangle, it is determined that the tensegrity robot has successfully completed a rolling motion; If the target point position is not within the triangle, the rolling axis and driving point are reselected based on the minimum direction principle according to the target point position of the tensegrity robot rolling, and the rolling motion is continued.

9. A tensegrity robot rolling motion system based on closed-loop control, characterized in that: include: Roll axis and drive point selection module: used to select the roll axis and drive point based on the minimum direction principle according to the target point position of the tensegrity robot roll; A module for obtaining the expected trajectory of the center of mass movement: used for planning the trajectory of the rolling angle and the rolling radius of the tensegrity robot according to the rolling axis and the driving point, and calculating the expected trajectory of the center of mass movement based on the planned trajectory of the rolling angle and the rolling radius of the tensegrity robot; The expected rolling motion module is used to track the expected trajectory of the center of mass motion of the tensegrity robot by using the tensegrity robot dynamics model considering the contact and collision conditions, and obtain the expected center of mass motion instruction; according to the expected center of mass motion instruction, the tensegrity robot is controlled to achieve the expected rolling motion with the expected rolling radius and rolling angle; Robot landing module: when the tensegrity robot in the desired rolling motion rolls into the falling stage, the closed-loop control law of the tensegrity robot rolling and falling stage is designed based on the partial feedback linearization control method to control the tensegrity robot to land; Rolling completion judgment module: used to judge whether the tensegrity robot reaches the set target point when landing. If it reaches the target point, it is determined that the tensegrity robot has successfully completed the continuous rolling task.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of a rolling motion method of a tensegrity robot based on closed-loop control as described in any one of claims 1 to 8 when executing the computer program.

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