Multi-robot system formation keeping method and multi-robot system

Abstract

The invention provides a multi-robot system formation keeping method and a multi-robot system, and the method comprises the steps: obtaining a formation keeping task which carries a plurality of task parameters; generating a motion path of each robot in the multi-robot system according to the plurality of task parameters, the generated optimal control function and at least one set constraint condition; and controlling the pilot robot and the at least one following robot to travel according to the motion path so as to complete the formation keeping task. According to the technical scheme provided by the embodiment of the invention, the motion path planning of the robot group can be realized in the known static environment, the motion path planning speed is accelerated, the motion path planning efficiency is improved, and the driving safety of the multi-robot system is improved, so that the multi-robot system can efficiently complete the formation keeping task.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-robot planning and control, and in particular to a multi-robot system formation maintaining method and a multi-robot system. Background Art

[0002] In a multi-agent system, the coordination of software and hardware systems and algorithms is the basis of autonomous planning. Robot motion planning refers to the process of formulating feasible motion trajectories and action sequences for robots that meet task requirements. Multi-robot motion planning is the motion planning of multiple robots with different starting positions and target positions. Compared with a single robot, a multi-robot system needs to collaborate during the planning process, and collaboration capability is an important indicator of the effectiveness of a multi-robot system. In recent years, with the continuous development of robotics technology, the application scenarios of multi-robot systems have become increasingly complex, and higher requirements have been placed on multi-robot motion planning. In related technologies, rule-based planning methods are usually used to solve and obtain motion paths, but the quality of the resulting motion paths is low, the path generation speed is slow, and the path generation efficiency is low. Summary of the invention

[0003] In view of the above problems, an embodiment of the present invention provides a multi-robot system formation maintaining method and a multi-robot system to solve the problems in the prior art that the motion path quality of the multi-robot system is low, the path generation speed is slow, and the path generation efficiency is low.

[0004] In a first aspect, an embodiment of the present invention provides a multi-robot system formation maintenance method, which is applied to a multi-robot system, wherein the multi-robot system includes a leading robot and at least one following robot, and the method includes:

[0005] Acquire a formation maintaining task, wherein the formation maintaining task carries multiple task parameters;

[0006] generating a motion path for each robot in the multi-robot system according to the plurality of task parameters, the generated optimal control function and the set at least one constraint condition;

[0007] The pilot robot and the at least one follower robot are controlled to travel along the motion path to complete the formation maintaining task.

[0008] In a possible implementation, the constraint condition includes an avoidance object constraint condition;

[0009] The avoidance object constraint condition is that the center coordinate distance is greater than the safety distance, wherein the center coordinate distance is the distance between the center coordinate of the current robot area and the center coordinate of the avoidance area, and the safety distance is the sum of the collision radius and the avoidance radius.

[0010] In a possible implementation, the multiple task parameters include starting position information of the pilot robot, target position information of the pilot robot, starting position information of the follower robot, at least one avoidance area information, and a distance parameter.

[0011] In a possible implementation manner, the constraint condition includes a formation keeping constraint condition, and the distance parameter includes a first distance parameter and a second distance parameter;

[0012] The formation maintaining constraint condition is that the target Euclidean distance is greater than the difference between the initial Euclidean distance and the first distance parameter, and the target Euclidean distance is less than the sum of the initial Euclidean distance and the second distance parameter.

[0013] In a possible implementation, the avoidance area is a minimum circumscribed circle generated according to the acquired outer coordinates of the avoidance object, the center coordinates of the avoidance area are the center of the avoidance area, and the avoidance radius is the radius of the avoidance area.

[0014] In a possible implementation, the method further includes:

[0015] Generate a minimum envelope circle according to the obtained peripheral coordinates of the current robot and the center coordinates of the current robot;

[0016] The collision radius is obtained by adding the radius of the minimum envelope circle to the set margin distance.

[0017] In a possible implementation, before generating the motion path of each robot in the multi-robot system according to the multiple task parameters, the generated optimal control function and the set at least one constraint condition, the method further includes:

[0018] The optimal control function is generated according to the acquired initial Euclidean distance, the target Euclidean distance, the angular velocity control amount and the set weight parameters.

[0019] In one possible implementation, the initial Euclidean distance includes the initial Euclidean distance between the pilot robot and each of the follower robots, and the initial Euclidean distance between at least one follower robot; the target Euclidean distance includes the target Euclidean distance between the pilot robot and each of the follower robots, and the target Euclidean distance between at least one follower robot.

[0020] In a second aspect, an embodiment of the present invention provides a multi-robot system, comprising a pilot robot and at least one follower robot, wherein the pilot robot and the at least one follower robot perform a multi-robot system formation maintaining method as described in the first aspect or any possible implementation of the first aspect.

[0021] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the multi-robot system formation maintaining method as described in the first aspect or any possible implementation of the first aspect.

[0022] In the technical solution provided by the embodiment of the present invention, motion path planning of a robot group can be realized in a known static environment, which speeds up the motion path planning speed, improves the motion path planning efficiency, and improves the driving safety of the multi-robot system, so that the multi-robot system can efficiently complete the formation maintenance task. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Shown is a flow chart of a multi-robot system formation maintaining method provided by an embodiment of the present invention.

[0024] Figure 2 Shown is a schematic diagram of a constraint condition provided by an embodiment of the present invention.

[0025] Figure 3 FIG. 4 is a schematic diagram of another constraint condition provided by an embodiment of the present invention.

[0026] Figure 4 Shown is a schematic diagram of a formation maintaining task provided by an embodiment of the present invention.

[0027] Figure 5 Shown is a schematic diagram of a motion path of a multi-robot system provided by an embodiment of the present invention.

[0028] Figure 6 A schematic diagram of a simulation result provided by an embodiment of the present invention.

[0029] Figure 7 A schematic diagram of the relative distance between robots provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer and more understandable, the present invention is further described below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Figure 1 A flowchart of a multi-robot system formation maintenance method provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0032] Step 101: Obtain a formation maintaining task, where the formation maintaining task carries multiple task parameters.

[0033] The steps in the embodiment of the present invention are applied to a multi-robot system, which includes a pilot robot and at least one follower robot.

[0034] In this step, in the embodiment of the present invention, the multiple task parameters include the starting posture information of the pilot robot, the target posture information of the pilot robot, the starting posture information of the follower robot, at least one avoidance area information and a distance parameter. The posture information includes the center coordinates and angle of the robot, and the avoidance area information includes the center coordinates and avoidance radius of the avoidance area.

[0035] Step 102: Generate a motion path for each robot in the multi-robot system according to a plurality of task parameters, the generated optimal control function and the set at least one constraint condition.

[0036] Optimal control theory is a discipline that uses mathematical methods to study how to make control systems work in an optimal way. Since the 1950s, optimal control theory has gradually developed, and its main solution methods are indirect method and direct method. Among them, indirect methods include variational method, maximum principle method, etc., and direct methods include shooting method, configuration method, etc. The indirect method is a method that uses analytical methods to solve optimal control problems. It requires the derivation of first-order necessary conditions and the solution of more complex differential equations. Compared with the indirect method, the direct method can directly optimize the performance indicators of the control system and has the advantages of lower initial value sensitivity and larger convergence radius. The pseudo-spectral method belongs to the configuration method, which solves the optimal control problem by converting the optimal control problem into a nonlinear programming problem. The advantage of the pseudo-spectral method is that it can handle general optimal control problems, and it also has high numerical accuracy and computational efficiency.

[0037] The Gaussian pseudospectral method improves the traditional pseudospectral method with higher accuracy, faster calculation speed and higher numerical stability. Studies have shown that for an optimal control problem with integral or differential dynamics, the equation or inequality conditions of nonlinear programming are completely equivalent to the discrete form of the first-order optimality conditions of the Hamiltonian boundary value problem. Therefore, the optimal control problem is transformed into a nonlinear programming problem, and the solution is obtained by solving this nonlinear programming problem. The Gaussian pseudospectral method can also handle general optimal control problems, including nonlinear, nonconvex, multi-objective and other problems, and has strong scalability.

[0038] In the embodiment of the present invention, the robot will be restricted by kinematics or dynamics when it moves. Since the robot's motion process on the ground is relatively complex, if you want to accurately describe the robot's motion state, you need to establish a complex differential equation group and use multiple state variables to describe its motion relationship. Under the premise of minimizing information loss, establishing a model that can accurately reflect the robot's kinematic characteristics or dynamic characteristics is the basis of robot motion planning. On the basis of the robot motion system equation, necessary constraints are added to solve the optimal motion trajectory and optimal action sequence for the robot to achieve a specific task. The kinematic model can describe the robot's motion process from the perspective of geometric relationships, including the changes in the robot's position and speed in space over time. Therefore, the trajectory obtained by planning based on the robot's kinematic model is feasible. Compared with the kinematic model, the dynamic model can also describe the robot's complex force process, but the complete dynamic model does not significantly increase the accuracy of motion planning solution, but will reduce the solution efficiency. Therefore, the kinematic model is used as a constraint in the embodiment of the present invention. The kinematic model is simpler and more efficient than the dynamic model. Considering the complex collaboration problem of multiple robots on the basis of the kinematic model is conducive to the design and solution of the planning algorithm.

[0039] In the embodiment of the present invention, a differential drive wheeled robot under nonholonomic constraints is used as an example for description, and the following assumptions are made:

[0040] 1) The robot moves along the center line of the vehicle body, and there is no relative sliding between the wheels and the ground;

[0041] 2) The turning radius of the robot is determined only by the ratio of the linear speeds of the wheels on both sides and the wheelbase;

[0042] 3) The robot motion is regarded as rigid body motion, and its motion takes place in a plane;

[0043] 4) Other factors that affect the operation of the robot, such as robot mass, ground friction, etc., are ignored.

[0044] In the embodiment of the present invention, the kinematic equation of the multi-robot is:

[0045]

[0046] Among them, θ i represents the heading angle of robot i, v i represents the linear velocity of robot i, ω i represents the angular velocity of robot i, represents the rate of change of the lateral position coordinate of robot i, represents the rate of change of the heading angle of robot i, Represents the rate of change of the heading angle of robot i.

[0047] In an embodiment of the present invention, the constraint condition includes an avoidance object constraint condition. The avoidance object constraint condition is that the center coordinate distance is greater than the safety distance, the center coordinate distance is the distance between the center coordinate of the current robot area and the center coordinate of the avoidance area, and the safety distance is the sum of the collision radius and the avoidance radius. The avoidance area is the minimum circumscribed circle generated based on the obtained outer coordinates of the avoidance object, the center coordinate of the avoidance area is the center of the avoidance area, and the avoidance radius is the radius of the avoidance area.

[0048] It can be understood that different task scenarios have different requirements for the accuracy of robot contour description. When the robot moves in a small range and high-risk scenario, the requirements for the accuracy of robot contour description are high, and the robot contour needs to be described in detail. In addition, an appropriate margin distance is generally left outside the robot contour to meet the robot's accurate obstacle avoidance requirements, improve obstacle avoidance efficiency and driving safety. In an embodiment of the present invention, a minimum envelope circle is generated based on the acquired peripheral coordinates of the current robot and the center coordinates of the current robot; the radius of the minimum envelope circle is added to the set margin distance to obtain a collision radius. Among them, the center coordinates of the current robot can be approximately described as the geometric midpoint of the current robot. The specific value of the margin distance can be set based on actual conditions, and the embodiment of the present invention is not limited to this.

[0049] As an optional solution, the avoidance area can be an obstacle area, that is, the area where the static obstacle is located. In this case, the avoidance area is the minimum circumscribed circle generated based on the outer coordinates of the static obstacle, the center coordinates of the avoidance area are the center coordinates of the obstacle area, the avoidance radius is the radius of the obstacle area, and the avoidance object constraint is the obstacle constraint.

[0050] In the embodiment of the present invention, the obstacle constraint condition is:

[0051] (xx 0 ) 2 +(yy 0 ) 2 ≥(R+R' 0 )

[0052] Among them, (x, y) represents the center coordinates of the current robot area, (x 0 ,y 0 ) represents the center coordinate of the obstacle area, R represents the collision radius, R 0 ' indicates the avoidance radius.

[0053] Figure 2 A schematic diagram of a constraint condition provided by an embodiment of the present invention, such as Figure 2As shown in the figure, the inner circle of the concentric circle is the minimum enveloping circle generated according to the peripheral coordinates of the current robot and the center coordinates of the current robot, the outer circle of the concentric circle is the current robot area, the radius of the outer circle is the collision radius, and the difference between the outer circle radius and the inner circle radius is the margin distance. The static obstacle is a closed area formed by points A, B, C, D, E, and F, and the obstacle area is the minimum circumscribed circle generated according to the coordinates of points A, B, C, D, E, and F. When the center coordinate distance is greater than the safety distance, the current robot can accurately avoid static obstacles in the scene and improve the driving safety of the multi-robot system.

[0054] As another optional solution, the avoidance area can be the collaborative robot area, that is, the area where the collaborative robot is located. In this case, the avoidance area is the minimum circumscribed circle generated according to the obtained peripheral coordinates of the collaborative robot, the center coordinates of the avoidance area are the center coordinates of the collaborative robot area, the avoidance radius is the radius of the collaborative robot area, and the avoidance object constraint condition is the collaborative robot constraint condition.

[0055] In the embodiment of the present invention, the constraints of the collaborative robot are:

[0056] (x i -x j ) 2 +(y i -y j ) 2 ≥(2*R)

[0057] Among them, (x i ,y i ) represents the center coordinate of the current robot i, (x j ,y j ) represents the center coordinate of collaborative robot j, R represents the radius of the current robot area, and also represents the radius of the collaborative robot area.

[0058] Figure 3 A schematic diagram of another constraint condition provided by an embodiment of the present invention, such as Figure 3As shown, the inner circle of the left concentric circles is the minimum enveloping circle generated according to the peripheral coordinates of the current robot and the center coordinates of the current robot, the outer circle of the left concentric circles is the current robot area, the radius of the outer circle is the collision radius, and the difference between the outer circle radius and the inner circle radius is the margin distance. The inner circle of the right concentric circles is the minimum enveloping circle generated according to the peripheral coordinates of the collaborative robot and the center coordinates of the collaborative robot, and the outer circle of the right concentric circles is the collaborative robot area. In an embodiment of the present invention, the current robot and the collaborative robot are isomorphic intelligent entities with the same performance. The current robot and the collaborative robot can cooperate with each other, exchange information, and jointly complete complex tasks. When the center coordinate distance is greater than the safety distance, the current robot can accurately avoid the collaborative robot in the scene to improve the driving safety of the multi-robot system.

[0059] In an embodiment of the present invention, the constraint condition includes a formation keeping constraint condition, and the distance parameter includes a first distance parameter and a second distance parameter. The formation keeping constraint condition is that the target Euclidean distance is greater than the difference between the initial Euclidean distance and the first distance parameter, and the target Euclidean distance is less than the sum of the initial Euclidean distance and the second distance parameter. Among them, the target Euclidean distance is used to indicate the Euclidean distance of the robots in the multi-robot system at time t. The initial Euclidean distance includes the initial Euclidean distance between the pilot robot and each follower robot, and the initial Euclidean distance between at least one follower robot; the target Euclidean distance includes the target Euclidean distance between the pilot robot and each follower robot, and the target Euclidean distance between at least one follower robot. For example, a multi-robot system includes a pilot robot A, a follower robot B and a follower robot C, then the initial Euclidean distance includes the initial Euclidean distance between the pilot robot A and the follower robot B, the initial Euclidean distance between the pilot robot A and the follower robot C, and the initial Euclidean distance between the follower robot B and the follower robot C; the target Euclidean distance includes the target Euclidean distance between the pilot robot A and the follower robot B, the target Euclidean distance between the pilot robot A and the follower robot C, and the target Euclidean distance between the follower robot B and the follower robot C.

[0060] In order to describe the formation-keeping behavior of a multi-robot system and meet the requirements of pseudo-spectral motion planning, a definition is given to represent the Euclidean distance between any two robots in the multi-robot system in the motion domain of the multi-robot system. Formation-keeping can be achieved if the Euclidean distance between the robots is kept within a certain range.

[0061] In the embodiment of the present invention, the formation maintaining constraint condition is:

[0062]

[0063] Among them, Δ 1 represents the first distance parameter, Δ 2 represents the second distance parameter, represents the initial Euclidean distance between robot i and robot j at time t = 0, and i ≠ j; represents the target Euclidean distance between robot i and robot j at time t, and i≠j. The first distance parameter is different from the second distance parameter, and the specific values ​​of the first distance parameter and the second distance parameter can be set according to actual conditions, which is not limited in the embodiment of the present invention.

[0064] It can be understood that in the formation maintenance task, the maintenance of the formation is very important and should be guided to ensure that the robot group has a tendency to return to the initial formation during the flight. Therefore, in the embodiment of the present invention, the optimal control function is generated according to the obtained initial Euclidean distance, target Euclidean distance, angular velocity control amount and set weight parameters.

[0065] In the embodiment of the present invention, the optimal control function is:

[0066]

[0067] Among them, (t 0 , t f ) is the entire motion time domain of the robot, t 0 represents the start time of the robot's movement, t f represents the end time of the robot's movement, β represents the weight function, ω i Indicates the angular velocity control amount of the robot.

[0068] In the embodiment of the present invention, the integral term is designed The purpose is to make the robots in the multi-robot system maintain their initial formation as much as possible and reduce angular velocity control to improve the smoothness of the robot's motion. The purpose is to reduce the angular velocity control of the robot. The larger β is, the higher the formation keeping task's requirement for keeping the formation, and the lower the energy consumption for angular velocity control; conversely, the smaller β is, the lower the formation keeping task's requirement for keeping the formation. In the embodiment of the present invention, angular velocity optimization is considered in the design of the optimal control function, so that the output angular velocity control amount is smoother, thereby improving the path generation quality.

[0069] Step 103: Control the leading robot and at least one following robot to move along the motion path to complete the formation maintaining task.

[0070] In the technical solution provided by the embodiment of the present invention, motion path planning of a robot group can be realized in a known static environment, which speeds up the motion path planning speed, improves the motion path planning efficiency, and improves the driving safety of the multi-robot system, so that the multi-robot system can efficiently complete the formation maintenance task.

[0071] The embodiment of the present invention designs relevant simulation experiments to verify the feasibility of the above constraints and the optimal control function in the formation keeping task.

[0072] Table 1 shows multiple mission parameters carried by the formation keeping mission.

[0073] Table 1

[0074]

[0075]

[0076] In the embodiment of the present invention, the multi-robot system includes a pilot robot (pilot robot A) and two follower robots, the two follower robots are respectively a first follower robot (follower robot B) and a second follower robot (follower robot C). As shown in Table 1 above, the starting posture information of the pilot robot is (1.25, 1.25, ), the target position information of the pilot robot is (7.25,7.25, ), the starting position information of the first follower robot is (1,1, ), the starting position information of the second follower robot is (1.5,1, ). The avoidance area includes the first avoidance area and the second avoidance area, and the avoidance area information includes the first avoidance area information and the second avoidance area information. As shown in Table 1 above, the first avoidance area information is (3,3,1.5), indicating that the center coordinates of the first avoidance area are (3,3) and the avoidance radius is 1.5. The second avoidance area information is (6,5,1), indicating that the center coordinates of the second avoidance area are (6,5) and the avoidance radius is 1.

[0077] Figure 4 A schematic diagram of a formation maintenance task provided by an embodiment of the present invention, such as Figure 4 As shown, the starting center coordinate A' of the leading robot A is (1.25, 1.25), the target center coordinate A" is (7.25, 7.25), the starting center coordinate B' of the following robot B is (1, 1), and the starting center coordinate C' of the following robot C is (1.5, 1). There are two avoidance areas in the driving scene of the multi-robot system, namely the first avoidance area and the second avoidance area. The center coordinates of the first avoidance area are (3, 3) and the avoidance radius is 1.5; the center coordinates of the second avoidance area are (6, 5) and the avoidance radius is 1.

[0078] In the embodiment of the present invention, the weight parameter β is set to 1 to generate a simulation result. Figure 5 A schematic diagram of a motion path of a multi-robot system provided by an embodiment of the present invention, such as Figure 5As shown, each robot in the multi-robot system can accurately avoid the avoidance area and maintain the formation to reach the finish line.

[0079] Figure 6 A schematic diagram of a simulation result provided by an embodiment of the present invention, such as Figure 6 As shown, x represents the horizontal coordinate of the robot center coordinate, y represents the vertical coordinate of the robot center coordinate, θ represents the heading angle of the robot, v represents the linear velocity of the robot, and ω represents the angular velocity of the robot. In the embodiment of the present invention, the angular velocity optimization is considered in the design of the optimal control function, so that the output angular velocity control amount is smoother, thereby improving the path generation quality.

[0080] Figure 7 A schematic diagram of the relative distance between robots provided by an embodiment of the present invention, such as Figure 7 As shown in the figure, in the entire motion domain of the multi-robot system, the distance between the pilot robot A and the follower robot B and the distance between the pilot robot A and the follower robot C are always maintained at about 0.35m, and the distance between the follower robot B and the follower robot C is always maintained at about 0.5m. It can be understood that the distance between the robots in the multi-robot system is relatively stable, indicating that the multi-robot system has good formation maintenance performance and can efficiently complete the formation maintenance task.

[0081] An embodiment of the present invention provides a multi-robot system, which includes a pilot robot and at least one follower robot. The pilot robot and the at least one follower robot perform the steps of the embodiment of the above-mentioned multi-robot system formation maintaining method. For specific descriptions, please refer to the embodiment of the above-mentioned multi-robot system formation maintaining method, which will not be repeated here.

[0082] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the steps of the embodiment of the above-mentioned multi-robot system formation maintaining method. For specific description, please refer to the embodiment of the above-mentioned multi-robot system formation maintaining method, which will not be repeated here.

[0083] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A multi-robot system formation maintenance method, characterized in that: Applied to a multi-robot system, the multi-robot system includes a pilot robot and at least one follower robot, the method includes: Acquire a formation maintaining task, wherein the formation maintaining task carries multiple task parameters; generating a motion path for each robot in the multi-robot system according to the plurality of task parameters, the generated optimal control function and the set at least one constraint condition; The pilot robot and the at least one follower robot are controlled to travel along the motion path to complete the formation maintaining task.

2. The method according to claim 1, characterized in that The constraint conditions include avoidance object constraint conditions; The avoidance object constraint condition is that the center coordinate distance is greater than the safety distance, wherein the center coordinate distance is the distance between the center coordinate of the current robot area and the center coordinate of the avoidance area, and the safety distance is the sum of the collision radius and the avoidance radius.

3. The method according to claim 1, characterized in that The multiple task parameters include the starting position information of the pilot robot, the target position information of the pilot robot, the starting position information of the follower robot, at least one avoidance area information and a distance parameter.

4. The method according to claim 3, characterized in that The constraint condition includes a formation keeping constraint condition, and the distance parameter includes a first distance parameter and a second distance parameter; The formation maintaining constraint condition is that the target Euclidean distance is greater than the difference between the initial Euclidean distance and the first distance parameter, and the target Euclidean distance is less than the sum of the initial Euclidean distance and the second distance parameter.

5. The method according to claim 2, characterized in that: The avoidance area is the minimum circumscribed circle generated according to the acquired outer coordinates of the avoidance object, the center coordinates of the avoidance area are the center of the avoidance area, and the avoidance radius is the radius of the avoidance area.

6. The method according to claim 2, characterized in that The method further comprises: Generate a minimum envelope circle according to the obtained peripheral coordinates of the current robot and the center coordinates of the current robot; The collision radius is obtained by adding the radius of the minimum envelope circle to the set margin distance.

7. The method according to claim 1, characterized in that Before generating the motion path of each robot in the multi-robot system according to the plurality of task parameters, the generated optimal control function and the set at least one constraint condition, the method further includes: The optimal control function is generated according to the acquired initial Euclidean distance, the target Euclidean distance, the angular velocity control amount and the set weight parameters.

8. The method according to claim 7, characterized in that The initial Euclidean distance includes the initial Euclidean distance between the pilot robot and each of the follower robots, and the initial Euclidean distance between at least one follower robot; the target Euclidean distance includes the target Euclidean distance between the pilot robot and each of the follower robots, and the target Euclidean distance between at least one follower robot.

9. A multi-robot system, characterized in that: The multi-robot system includes a pilot robot and at least one follower robot, and the pilot robot and the at least one follower robot perform the multi-robot system formation maintaining method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the multi-robot system formation maintaining method according to any one of claims 1 to 8.

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