A method and device for generating movement control signals of a tensegrity robot

Abstract

The present invention discloses a method and device for generating movement control signals for a tensegrity robot, belonging to the field of robot control technology. The method comprises: selecting a portion of the cables of the tensegrity robot as active cables and the remaining portion as passive cables; inputting the initial values ​​of the gait variables of the active cables into an optimization algorithm for iteration to obtain updated values ​​of the gait variables of the active cables, and then inputting the updated values ​​of the gait variables of the active cables into the optimization algorithm for repeated iteration until a specified number of iterations is reached; fine-tuning and optimizing the gait variables through multiple rounds of iteration; calculating the active cable update control signals and their evaluation parameters corresponding to the updated values ​​of the gait variables of the active cables in each round of iteration to determine the active cable target control signals; the gait variables determined in this way and the corresponding active cable target control signals are used to control the active cables and drive the passive cables to perform gait movements, thereby accurately controlling the rapid walking movement of the tensegrity robot.

Description

Technical Field

[0001] The present invention belongs to the field of robot control technology, and more specifically, relates to a method and device for generating movement control signals of a tensegrity robot. Background Art

[0002] Tensegrity robots are a type of robot inspired by tensegrity structures. A tensegrity structure is a structural system that achieves stability and balance through the interaction of separate rigid components (such as rods or beams) and continuous flexible components (such as ropes or cables). Tensegrity structures are lightweight and strong. Tensegrity structures are usually light in weight, but can withstand large external loads, are easy to fold, flexible and adaptable (due to the characteristics of their flexible components, such structures can adapt to complex environments and deformations), and have efficient force transmission (force is transmitted through flexible components, allowing the entire structure to effectively disperse and withstand external forces). Therefore, tensegrity robots can effectively save launch costs when exploring complex environments in outer space, and have high adaptability and impact resistance, making them an effective robot for exploring extraterrestrial bodies. The robot usually produces deformation and movement by controlling the length of flexible cables or rods.

[0003] The current motion control method for tensegrity robots on the ground mainly uses deformation to change the center of gravity position and then generate torque for rolling, which has the problems of low movement efficiency and poor control accuracy. Summary of the Invention

[0004] In response to the above-mentioned defects or improvement needs of the prior art, the present invention provides a method and device for generating movement control signals of a tensegrity robot, the purpose of which is to solve the technical problems of low movement efficiency and poor control accuracy of the existing tensegrity robot.

[0005] To achieve the above objectives, according to one aspect of the present invention, a method for generating movement control signals for a tensegrity robot is provided, comprising:

[0006] S1: Selecting a portion of all cables of the tensegrity robot as active cables and the remaining portions as passive cables;

[0007] S2: determining each gait action in the movement behavior of the tensegrity robot; setting an initial range of gait variables corresponding to each gait action; generating initial values ​​of the gait variables of each active cable within the initial range; the gait variables including: a time variable t representing the time taken to complete each gait action, an active cable length variable X representing the change in the current length of the active cable compared to the original length, an active cable extension variable H representing whether the active cable is extended or shortened, and a correction variable G for improving trajectory deviation when the tensegrity robot moves straight;

[0008] S3: inputting the initial value of the gait variable of each active cable into the optimization algorithm for iteration to obtain an updated value of the gait variable of each active cable, and then inputting the updated value of the gait variable of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached;

[0009] S4: calculating each active cable update control signal and its corresponding evaluation parameter corresponding to the updated value of the gait variable of each active cable in each iteration;

[0010] S5: Using the active cable update control signal corresponding to the evaluation parameter satisfying the preset condition as the active cable target control signal to control the active cable and drive the passive cable to perform the gait action.

[0011] In one embodiment, in S1: the principle for selecting the active cables is: selecting a waist cable that can change the tilt posture of the tensegrity robot and a bottom cable that is necessary to move the end of the tensegrity robot in contact with the ground as the active cables.

[0012] In one embodiment, the active cable length variable X, the active cable expansion and contraction variable H, and the correction variable G are all percentages; the product of the active cable length variable X and the corresponding original length of the active cable represents the change in the length of the active cable compared to the original length of the active cable in the current round of iteration; the active cable expansion and contraction variable H has the same amplitude as the active cable length variable X, and the sign of the active cable expansion and contraction variable H is positive or negative. When positive, it indicates that the length is extended relative to the initial moment, and when negative, it indicates that the length of the active cable is shortened relative to the initial moment.

[0013] In one embodiment, the S4 includes:

[0014] interpolating the time series of changes in the lengths of the active cables corresponding to the updated values ​​of the gait variables of the active cables in each round of iteration to obtain active cable update control signals corresponding to the changes in the lengths of the active cables over time;

[0015] The active cable update control signal is input into a simulation program to obtain the coordinates after the movement, and the coordinates after the movement and the coordinates before the movement are input into a fitness function for calculation to obtain the fitness representing the evaluation parameter corresponding to the active cable update control signal.

[0016] In one embodiment, the fitness function is fit = (X(end)-X(0))-abs(Y(end)-Y(0)), where X(end) and Y(end) respectively represent the coordinates of the horizontal and vertical axes at the end of the robot's movement, and X(0) and Y(0) respectively represent the coordinates of the horizontal and vertical axes at the beginning of the robot's movement; abs represents the absolute value function.

[0017] In one embodiment, the step S5 includes: selecting the active search update control signal corresponding to the maximum fitness as the active search target control signal.

[0018] In one embodiment, the optimization algorithm is a genetic algorithm, a particle swarm algorithm or an ant colony algorithm.

[0019] According to another aspect of the present invention, there is provided a device for generating movement control signals for a tensegrity robot, comprising:

[0020] a selection module for selecting a portion of all cables of the tensegrity robot as active cables and the remaining portion as passive cables;

[0021] a setting module for determining each gait action in the movement behavior of the tensegrity robot; setting an initial range of gait variables corresponding to each gait action; generating initial values ​​of the gait variables of each active cable within the initial range; the gait variables including: a time variable t representing the time taken to complete each gait action; an active cable length variable X representing the change in the current length of the active cable compared to the original length; an active cable extension variable H representing whether the active cable is extended or shortened; and a correction variable G for improving trajectory deviation when the tensegrity robot moves straight;

[0022] an optimization module, configured to input the initial values ​​of the gait variables of each active cable into an optimization algorithm for iteration, obtain updated values ​​of the gait variables of each active cable, and then input the updated values ​​of the gait variables of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached;

[0023] a calculation module, configured to calculate each active cable update control signal and its corresponding evaluation parameter corresponding to the update value of each active cable gait variable in each iteration;

[0024] The determination module is configured to use the active cable update control signal corresponding to the evaluation parameter satisfying the preset condition as the active cable target control signal to control the active cable and drive the passive cable to perform the gait action.

[0025] According to another aspect of the present invention, there is provided a method for controlling movement of a tensegrity robot, comprising:

[0026] Based on the motion control signal generation method of the tensegrity robot, an active cable target control signal is obtained;

[0027] The active cable target control signal is used to control the active cable of the tensegrity robot to extend and retract and drive the passive cable to move, so as to perform corresponding gait movements.

[0028] According to another aspect of the present invention, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for generating a movement control signal of a tensegrity robot or the method for controlling the movement of the tensegrity robot.

[0029] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the method for generating a movement control signal of a tensegrity robot or the method for controlling the movement of the tensegrity robot.

[0030] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0031] (1) The present invention provides a method for generating movement control signals of a tensegrity robot, wherein some of the cables of the tensegrity robot are selected as active cables, and only some of the cables need to be controlled, thereby reducing the control complexity; the initial values ​​of the gait variables of each active cable are input into an optimization algorithm for iteration to obtain updated values ​​of the gait variables of each active cable, and then the updated values ​​of the gait variables of the active cables are input into the optimization algorithm for repeated iteration until a specified number of iterations is reached; the gait variables are fine-tuned and optimized through multiple rounds of iteration; the active cable update control signals and their evaluation parameters corresponding to the updated values ​​of the gait variables of each active cable in each round of iteration are calculated; the active cable target control signals are selected from the active cable target control signals according to the evaluation parameters; the gait variables and their corresponding active cable target control signals determined in this way can accurately control the tensegrity robot to move quickly, thereby solving the technical problems of low movement efficiency and poor control accuracy of the existing tensegrity robot.

[0032] (2) The principle for selecting the active cables in this solution is to select the waist cables that can change the tilt posture of the tensegrity robot and the bottom cables that are necessary to move the tensegrity robot to contact the ground as the active cables. The advantage is that the number of active cables can be reduced, and only the above-mentioned active cables need to be selected to complete the movement control of the tensegrity robot, thereby reducing the calculation amount of the optimization algorithm and the control difficulty.

[0033] (3) The active cable length variable X, the active cable extension variable H, and the correction variable G described in this scheme are all percentage numbers. The advantage is that they can clearly and simply represent the length state of each active cable in the motion gait. The use of percentages makes it applicable to the original lengths of different active cables, which facilitates the unification of the length variable range.

[0034] (4) In this scheme, the time series of the length changes of each active cable corresponding to the updated value of the gait variable of each active cable in each round of iteration are interpolated. The advantage is that a continuous control signal can be obtained. Different control signals can be obtained by using different interpolation methods. For example, the use of quadratic function interpolation will make the control signal smoother. Furthermore, the updated control signal of the active cable is input into the simulation program to obtain the coordinates after movement, and the coordinates after movement and the coordinates before movement are input into the fitness function to calculate and obtain the fitness representing the evaluation parameter. The advantage of this method is that the control result of the control signal is evaluated by the simulation program, so that the evaluation of the control signal is more reliable without the need for actual prototype verification. At the same time, it can speed up the optimization iteration of the entire control signal and improve the fitness of the control signal.

[0035] (5) The fitness function in this scheme is set to fit = (X(end)-X(0))-abs(Y(end)-Y(0)). Its advantage is that it allows the robot to move straight in the specified direction and reduce the deviation from the specified direction.

[0036] (6) In this scheme, the active search update control signal corresponding to the maximum fitness is selected as the active search target control signal. The advantage is that the computational complexity is low and the optimal active search target control signal can be quickly found.

[0037] (7) The optimization algorithm described in this scheme is a genetic algorithm, a particle swarm algorithm or an ant colony algorithm. The above algorithms are all mature and stable optimization algorithms that can improve the stability of the mobile control signal generation method of the entire tensegrity robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flow chart of a method for generating movement control signals for a tensegrity robot provided in Example 1 of the present invention;

[0039] Figure 2 2 is a schematic structural diagram of a three-rod, nine-cable prismatic tensegrity robot provided in Example 1 of the present invention;

[0040] Figure 3 This is a simulation diagram of the movement effect of the three-rod and nine-cable prismatic tensegrity robot provided in Example 1 of the present invention moving straight in accordance with the first movement mode;

[0041] Figure 4 This is a simulation diagram of the movement effect corresponding to the straight movement of the three-rod and nine-cable prismatic tensegrity robot provided in Example 1 of the present invention according to the second movement mode. DETAILED DESCRIPTION

[0042] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0043] Example 1

[0044] The present embodiments are all described using a three-rod and nine-cable prismatic tensegrity robot as an example. It should be noted that the number of rods and cables of the tensegrity robot of the present application is not limited, and tensegrity robots with other numbers of rods and cables can also generate movement control signals according to the following method.

[0045] This embodiment provides a method for generating a movement control signal of a tensegrity robot, such as Figure 1 As shown, the following steps S1-S5 are included.

[0046] S1: Select some cables from all the cables of the tensegrity robot as active cables and the remaining cables as passive cables.

[0047] Among them, according to the structural characteristics and force analysis of the three-rod, nine-cable prismatic robot, the robot's moving gait is designed, and some cables are selected from all the cables of the tensegrity robot as active cables, which can be controlled by motors and can actively change their length; the rest are passive cables, that is, cables without motor control and can only passively change their length.

[0048] As an optional implementation, in S1: the principle for selecting the active cables is: selecting the waist cable that can change the tilt posture of the tensegrity robot and the bottom cable necessary to move the tensegrity robot to contact the ground as the active cables.

[0049] Take the three-rod and nine-cable tensegrity robot as an example. Its structure is as follows: Figure 2As shown, the robot consists of three rods and nine cables. Numbers 1, 2, and 3 represent bottom cables, numbers 4, 5, and 6 represent top cables, and numbers 7, 8, and 9 represent waist cables. Numbers B1, B2, and B3 represent the rod structure. Numbers F1, F2, and F3 represent the rod's feet that contact the ground, with F3 representing the front foot and F1 and F2 representing the rear foot. Each rod has two ends. The waist cable connects the bottom end (the end in contact with the ground) and the top end (the end not in contact with the ground). The bottom cable connects the bottom end, and the top cable connects the top end. When the three-rod, nine-cable tensegrity robot is positioned along the forward direction, that is, when the midline of the equilateral triangle formed by the three bottom cables coincides with the forward direction, the rod ends and waist cables are divided into two equal parts: the rod end closer to the front is the front end, and the rod end closer to the rear is the rear end. Similarly, the waist cable closer to the front is the front waist cable, and the waist cable closer to the rear is the rear waist cable. The principle for selecting the active and passive cables is that the necessary active cables include the waist cables that can change the tilt posture of the three-rod nine-cable prismatic robot (e.g. Figure 2 7, 8, and 9) and the necessary bottom cables (e.g. Figure 2 1, 2, and 3) in [1], and the rest can be passive cables. The more active cables selected, the better the control effect may be, but it will also increase the computational complexity of the optimization algorithm.

[0050] S2: Determine each gait action in the movement behavior of the tensegrity robot; set the initial range of the gait variables corresponding to each gait action; wherein, the gait variables are set according to the movement gait of the robot and the selected active cable, and the initial value of the gait variable of each active cable is generated within the initial range by making a robot movement gait table and setting the initial range of the gait variables; the gait variables include: a time variable t representing the time consumed to complete each gait action, an active cable length variable X representing the change in the current length of the active cable compared to the original length, an active cable extension variable H representing whether the active cable is extended or shortened, and a correction variable G for improving the trajectory deviation when the tensegrity robot moves straight.

[0051] The idea behind the design of the straight-ahead gait motion is as follows: first, the waist cable is changed to cause the three-rod, nine-cable prismatic tensegrity robot to tilt as a whole in the forward direction, thereby generating a pressure difference between the front and rear rod ends of the three-rod, nine-cable prismatic tensegrity robot in contact with the ground. Next, the active cables at the front and rear rod ends are contracted, causing the rear rod end to move forward. At this point, the tensegrity robot tilts backward as a whole, and the active cables between the front and rear rod ends are restored to their initial length, causing the front rod end to move forward. The robot then resumes its forward tilt, completing a gait cycle.

[0052] As an optional implementation, the active cable length variable X, the active cable expansion and contraction variable H, and the correction variable G are all percentages; the product of the active cable length variable X and the corresponding original length of the active cable represents the length of the active cable in the current iteration; the active cable expansion and contraction variable H has the same amplitude as the active cable length variable X, and the sign of the active cable expansion and contraction variable H is positive or negative. When positive, it indicates an extension relative to the initial length, and when negative, it indicates a shortening relative to the initial length.

[0053] Among them, the gait variables are X i 、H i , G i , t i Four different gait variables, X i 、H i , G i The product of the gait variable and the initial length of the corresponding active cable can represent the change in the length of the active cable compared to the initial length in the current gait phase. A positive value indicates that the length is extended relative to the initial moment, while a negative value indicates that the active cable is shortened relative to the initial moment. i In order to improve the trajectory deviation of the three-rod and nine-cable prismatic tensegrity robot when it moves straight, t i The time spent on the action in this gait phase, where X i >0,H i Not sure whether it is positive or negative, 0<G i <1, t i >0. G i The purpose is to correct the behavior of the three-rod and nine-cable prismatic tensegrity robot that deviates from the predetermined trajectory to the left due to the leftward deviation of the center of gravity when the robot leans forward or moves forward. During the iteration process, you can take a result to observe whether the robot deviates to the left or right, or increase the G of the corresponding waist cable according to the direction in which the robot's center of gravity deviates from the predetermined trajectory. i Correct the variables so that the robot can move in the desired direction.

[0054] The length state variables in the gait variables are divided into X i 、H i , G i , where X i (X1, X2, X3...) are used to represent the state parameters of the active cables, whether they are contracted or stretched. For example, when a three-rod, nine-cable prismatic tensegrity robot leans forward, the states of the three waist cables are clear, and the front waist cable is contracted (with -X for contraction). i Indicated), the back waist cable is extended (extension is indicated by X i express).

[0055] Length status parameter H i(H1, H2, H3…) are state parameters used to indicate whether the unknown active cable is in a contraction or extension state. The positive or negative value of the parameter is uncertain. In some cases where it is difficult to determine the length change state of the active cable, the parameter can be used to indicate the length state of the active cable.

[0056] Length status parameter G i (G1, G2, G3...) are used to represent adjustment parameters to correct the problem of the three-rod nine-cable prismatic tensegrity robot deviating from the straight trajectory when moving straight. This is mainly for the waist cable. Since the center of gravity of the three-rod nine-cable prismatic tensegrity robot is not actually at the center of the bottom triangle, for example, when the robot leans forward, the length of the waist cable needs to be adjusted so that the center of gravity coincides with the straight direction. At this time, the left waist cable length state parameter is subtracted from X i G i This improves the right-leaning posture of the three-bar, nine-cable prismatic tensegrity robot so that the pressure between the two rear feet and the ground is equal. This ensures that the rear feet move the same distance when moving forward, ensuring that the straight trajectory does not deviate.

[0057] It should be noted that the initial range of each gait variable is determined according to the actual hardware conditions, where X i and H i The size setting should ensure that the length of the active cable does not exceed the range of the active cable in the actual hardware. The signal generation method is interpolation, that is, the designed gait determines the state at the end of each gait stage. According to the gait table, the time series of the active cable length change can be obtained. By interpolating the time series of the length change, a continuous active cable length change control signal is generated.

[0058] S3: Inputting the initial values ​​of the gait variables of each active cable into the optimization algorithm for iteration to obtain updated values ​​of the gait variables of each active cable. Then, inputting the updated values ​​of the gait variables of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached. The optimization algorithm may be a genetic algorithm, a particle swarm algorithm, or an ant colony algorithm.

[0059] S4: Calculating each active cable update control signal and its corresponding evaluation parameter corresponding to the updated value of the gait variable of each active cable in each iteration.

[0060] As an optional implementation, S4 includes: interpolating the time series of changes in the lengths of the active cables corresponding to the updated values ​​of the gait variables of the active cables in each round of iteration to obtain an active cable update control signal corresponding to the change in the length of the active cables over time; inputting the active cable update control signal into a simulation program to obtain the coordinates after movement, inputting the coordinates after movement and the coordinates before movement into a fitness function for calculation, and obtaining the fitness representing the evaluation parameter corresponding to the active cable update control signal.

[0061] Among them, the simulation needs to consider stopping the simulation when it is about to tilt and regenerating a new control signal through the genetic algorithm. The judgment condition for whether to stop can be set to that the vertical height difference between the upper end of each pole off the ground and the lower end of the pole touching the ground is greater than a fixed value. This fixed value can be set freely, depending on the tilt state that you want to abandon.

[0062] As an optional implementation, the fitness function is fit = (X(end)-X(0))-abs(Y(end)-Y(0)), where X(end) and Y(end) respectively represent the coordinates of the horizontal and vertical axes at the end of the robot's movement, and X(0) and Y(0) respectively represent the coordinates of the horizontal and vertical axes at the beginning of the robot's movement; abs represents the absolute value function.

[0063] S5: The active cable update control signal corresponding to the evaluation parameter satisfying the preset conditions is used as the active cable target control signal; specifically, the active cable gait variable with the largest fitness in the population is selected as the final active cable gait variable, and then the time series signal of the active cable length change is obtained according to the robot movement gait table; the time series signal of the active cable length change is interpolated to obtain the control signal of each active cable length changing with time, so as to control the active cable and drive the passive cable to perform the gait action.

[0064] Furthermore, if fitness is used to represent the evaluation parameter, S5 includes: selecting the active search update control signal corresponding to the maximum fitness as the active search target control signal.

[0065] It should be noted that the active cable target control signal also needs to consider the maximum change speed of the active cable. If the control signal active cable change speed exceeds the maximum change speed that the active cable can achieve in the hardware, a new signal is generated through the optimization algorithm until the hardware can meet the actual length change speed.

[0066] The method for generating movement control signals for a tensegrity robot provided in this embodiment selects some of the cables as active cables from all cables through structural and force analysis, and the remaining cables as passive cables. The shape and posture of the robot are changed by changing the length of the active cables through motor drive, thereby changing the position of the center of gravity, thereby changing the pressure of the rod end on the ground, thereby changing the maximum friction between the rod end and the ground, and realizing the movement of the robot on flat ground and uphill according to the set movement gait. The gait variables are iteratively optimized through an optimization algorithm, and the time series of the length change of each active cable is obtained according to the gait table, and then the length control signal of the active cable is generated by interpolation. Compared with the traditional unsupervised control algorithm, the method of the present invention generates feasible control signals faster and improves the movement speed and control accuracy of the three-rod and nine-cable prismatic tensegrity robot.

[0067] The following describes the process of generating active cable control signals corresponding to the straight movement of the tensegrity robot using two movement modes.

[0068] The first movement mode: When the movement behavior moves forward, the gait action includes: overall forward leaning and periodic first action combination. The first action combination includes: moving the rear two feet forward, moving the front foot forward and restoring the forward leaning. The movement effect simulation is as follows Figure 3 As shown, the following describes the generation process of the movement control signal generation of the tensegrity robot.

[0069] First, determine the active cables and passive cables: According to the structural characteristics of the three-rod and nine-cable tensegrity robot, the active cables that need to be driven to change the tilt posture (forward, backward, etc.) are three waist cables, and the cables that need to move the feet are two bottom cables, a total of five active cables, and the remaining four are passive cables.

[0070] Then, a locomotion gait was designed based on the selected active cables. The complete gait cycle consists of a transition from an initial neutral state to an overall forward leaning state. This state is not a cyclic gait, but rather a preparatory gait for movement. This is followed by a forward-moving bipedal gait, followed by a forward-moving forefoot gait, and finally a return to forward leaning. When the three-bar, nine-cable tensioned robot moves straight, these four gaits—except for the first, which is executed only once—are executed in a cyclical manner, allowing the robot to move straight continuously. The designed gait table (Table 1) is as follows:

[0071] Table 1

[0072]

[0073] Furthermore, the initial parameters in the table are determined according to the designed gait and the initial length of the active cable. i The parameter range is set to [0,0.6], H i The parameter range is set to [-0.6, 0.6], G iThe parameter range is set to [0, 0.2]. Each parameter value is randomly obtained within the parameter range as the initial value for the genetic algorithm iteration. The parameters in the gait parameter table are used to interpolate and obtain a continuous active cable length change signal. The four time variables and eight length state variables in this gait are used as variables to be optimized in the genetic algorithm. The fitness function is fit = (X(end)-X(0))-abs(Y(end)-Y(0)), where X(0), Y(0), and Y(end) are the initial X and Y positions of the center of the triangle formed by the three rod ends connecting the ground and the position after a complete gait. The physical structure model in the simulation program Simulink was exported from SolidWorks, and the motor adopted a position-voltage dual-loop PID control. Finally, through continuous iteration of the priority algorithm, the optimal gait parameter results were obtained.

[0074] The second movement mode: When the movement behavior is forward, the gait action can also include: right forward leaning and periodic second action combination; the second action combination includes: moving the left foot forward, leaning forward to the left, moving the right foot forward, leaning forward as a whole, moving the front foot forward and restoring the right forward leaning. The movement effect simulation is as follows Figure 4 As shown, the following describes the generation process of the motion control signal for the tensegrity robot:

[0075] First, determine the active cables and passive cables: According to the structural characteristics of the three-rod and nine-cable tensegrity robot, the active cables that need to be driven to change the tilt posture (forward, backward, etc.) are three waist cables, and the cables that need to move the feet are two bottom cables, a total of five active cables, and the remaining four are passive cables.

[0076] Then, a gait was designed based on the selected active cables: the complete gait cycle was designed to transition from an initial neutral state to a right-leaning forward state. This state is not a cyclic gait, but rather a preparatory gait for starting movement. This is followed by a gait movement with the left foot moving forward, followed by a gait movement with a left-leaning forward lean, a right-foot moving forward, a full-body forward lean, a forward movement of the front foot, and finally a return to a right-leaning forward lean. When the three-bar, nine-cable tensioned robot moves straight, these seven gait movements, except for the first one, which is executed only once, are repeated in a cycle of the remaining six, allowing the robot to move straight continuously. The designed gait table (Table 1) is as follows:

[0077] Table 2

[0078]

[0079] Then, determine the initial parameters in the table based on the designed gait and the initial length of the active cable. i The parameter range is set to [0,0.6], Hi The parameter range is set to [-0.6, 0.6]. Parameters in the gait parameter table are interpolated to obtain a continuous active cable length change signal. The seven time variables and 18 length state variables in this gait are used as variables to be optimized in the genetic algorithm. The fitness function is: fit = (X(end) - X(0)) - abs(Y(end) - Y(0)), where X(0), Y(0), X(end), and Y(end) are the initial X and Y positions of the center of the triangle formed by the three rod ends of the three-rod, nine-cable prismatic tensegrity robot in contact with the ground and the position after the completion of a complete gait. The physical structure model in Simulink was exported from SolidWorks, and the motors were controlled using a position-voltage dual-loop PID control. Optimal gait parameter results were obtained through continuous iteration of the genetic algorithm.

[0080] Example 2

[0081] The present embodiment provides a mobile control signal generating device for a tensegrity robot, comprising the following modules: a selection module for selecting a portion of all cables of the tensegrity robot as active cables and the remaining portion as passive cables; a setting module for determining each gait action in the mobile behavior of the tensegrity robot; setting the initial range of the gait variables corresponding to each gait action; generating the initial value of the gait variable of each active cable within the initial range; the gait variables include: a time variable t representing the time taken to complete each gait action, an active cable length variable X representing the change in the current length of the active cable compared to the original length, an active cable extension variable H representing whether the active cable is extended or shortened, and a correction variable for improving the trajectory deviation of the tensegrity robot when it moves straight. A positive variable G; an optimization module, configured to input the initial values ​​of the gait variables of each active cable into the optimization algorithm for iteration to obtain updated values ​​of the gait variables of each active cable, and then input the updated values ​​of the gait variables of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached; a calculation module, configured to calculate the updated control signals of each active cable and their corresponding evaluation parameters corresponding to the updated values ​​of the gait variables of each active cable in each iteration; a determination module, configured to use the updated control signals of the active cables corresponding to the evaluation parameters satisfying preset conditions as the target control signals of the active cables, so as to control the active cables and drive the passive cables to perform the gait movements.

[0082] Example 3

[0083] This embodiment provides a movement control method for a tensegrity robot, comprising: obtaining an active cable target control signal based on a movement control signal generation method for a tensegrity robot; and controlling the tensegrity robot to perform corresponding gait movements using the active cable target control signal.

[0084] Example 4

[0085] This embodiment provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a method for generating a movement control signal of a tensegrity robot or steps of a movement control method of a tensegrity robot is implemented.

[0086] Example 5

[0087] This embodiment provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of a method for generating a movement control signal of a tensegrity robot or a movement control method of a tensegrity robot when the computer program is executed by a processor.

[0088] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for generating a motion control signal for a tensegrity robot, characterized in that: include: S1: Selecting a portion of all cables of the tensegrity robot as active cables and the remaining portions as passive cables; S2: determining each gait action in the movement behavior of the tensegrity robot; setting an initial range of a gait variable corresponding to each gait action; generating initial values ​​of the gait variables of the active cables within the initial range; The gait variables include: a time variable t representing the time taken to complete each gait action, an active cable length variable X representing the change in the current length of the active cable compared to the original length, an active cable extension variable H representing whether the active cable is extended or shortened, and a correction variable G for improving the trajectory deviation of the tensegrity robot when moving straight; S3: inputting the initial value of the gait variable of each active cable into the optimization algorithm for iteration to obtain an updated value of the gait variable of each active cable, and then inputting the updated value of the gait variable of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached; S4: calculating each active cable update control signal and its corresponding evaluation parameter corresponding to the updated value of the gait variable of each active cable in each iteration; S5: Using the active cable update control signal corresponding to the evaluation parameter satisfying the preset condition as the active cable target control signal to control the active cable and drive the passive cable to perform the gait action.

2. The method for generating a motion control signal for a tensegrity robot according to claim 1, wherein: In S1, the principle for selecting the active cables is to select a waist cable that can change the tilt posture of the tensegrity robot and a bottom cable that is necessary to move the end of the tensegrity robot in contact with the ground as the active cables.

3. The method for generating a motion control signal for a tensegrity robot according to claim 1, wherein: The active cable length variable X, active cable extension variable H and correction variable G are all percentages; The product of the active cable length variable X and the corresponding original length of the active cable represents the change in the length of the active cable in the current iteration compared to the original length of the active cable; The active cable expansion and contraction variable H has the same amplitude as the active cable length variable X. The sign of the active cable expansion and contraction variable H is positive or negative. When it is positive, it indicates that the length is extended relative to the initial moment, and when it is negative, it indicates that the active cable is shortened relative to the initial moment.

4. The method for generating a movement control signal of a tensegrity robot according to claim 1, wherein: The S4 includes: interpolating the time series of changes in the lengths of the active cables corresponding to the updated values ​​of the gait variables of the active cables in each round of iteration to obtain active cable update control signals corresponding to the changes in the lengths of the active cables over time; The active cable update control signal is input into a simulation program to obtain the coordinates after the movement, and the coordinates after the movement and the coordinates before the movement are input into a fitness function for calculation to obtain the fitness representing the evaluation parameter corresponding to the active cable update control signal.

5. The method for generating a movement control signal of a tensegrity robot according to claim 4, wherein: The fitness function is fit = (X(end)-X(0))-abs(Y(end)-Y(0)), where X(end) and Y(end) represent the coordinates of the horizontal and vertical axes at the end of the robot's movement, respectively, and X(0) and Y(0) represent the coordinates of the horizontal and vertical axes at the beginning of the robot's movement; abs represents the absolute value function.

6. The method for generating a movement control signal of a tensegrity robot according to claim 5, wherein: The step S5 includes: selecting the active search update control signal corresponding to the maximum fitness as the active search target control signal.

7. The method for generating a movement control signal for a tensegrity robot according to claim 1, wherein: The optimization algorithm is a genetic algorithm, a particle swarm algorithm or an ant colony algorithm.

8. A device for generating movement control signals for a tensegrity robot, characterized in that: include: a selection module for selecting a portion of all cables of the tensegrity robot as active cables and the remaining portion as passive cables; A setting module is configured to determine each gait action in the movement behavior of the tensegrity robot; and set an initial range of a gait variable corresponding to each gait action; generating initial values ​​of the gait variables of the active cables within the initial range; The gait variables include: a time variable t representing the time taken to complete each gait action, an active cable length variable X representing the change in the current length of the active cable compared to the original length, an active cable extension variable H representing whether the active cable is extended or shortened, and a correction variable G for improving the trajectory deviation of the tensegrity robot when moving straight; an optimization module, configured to input the initial values ​​of the gait variables of each active cable into an optimization algorithm for iteration, obtain updated values ​​of the gait variables of each active cable, and then input the updated values ​​of the gait variables of the active cable into the optimization algorithm for repeated iteration until a specified number of iterations is reached; a calculation module, configured to calculate each active cable update control signal and its corresponding evaluation parameter corresponding to the update value of each active cable gait variable in each iteration; The determination module is configured to use the active cable update control signal corresponding to the evaluation parameter satisfying the preset condition as the active cable target control signal to control the active cable and drive the passive cable to perform the gait action.

9. A method for controlling the movement of a tensegrity robot, characterized in that: include: Based on the method for generating a movement control signal of a tensegrity robot according to any one of claims 1 to 7, an active cable target control signal is obtained; The active cable target control signal is used to control the active cable of the tensegrity robot to extend and retract and drive the passive cable to move, so as to perform corresponding gait movements.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the processor implements the steps of the method for generating a movement control signal for a tensegrity robot according to any one of claims 1 to 7 or the method for controlling the movement of a tensegrity robot according to claim 9.

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