Path planning algorithm for multi-spherical robot formation process

Abstract

The present invention provides a path planning algorithm for the formation process of multiple high-speed rolling spherical robots based on an improved artificial potential field method, which belongs to the field of intelligent algorithm optimization. First, the starting position distribution, map information, and expected formation information of each spherical robot are obtained; according to the starting position, map information, and expected formation information of each spherical robot, an improved artificial potential field method of gravity and repulsion is proposed based on the traditional artificial potential field method to plan the movement path of each spherical robot and finally form a formation. Simulation research shows that the present invention can realize the formation task of multiple high-speed rolling spherical robots, verifying the effectiveness and practicality of the algorithm.

Description

Technical Field

[0001] The invention belongs to the field of intelligent algorithm optimization and relates to a path planning algorithm for a multi-spherical robot formation process based on an improved artificial potential field method. Background Art

[0002] With the rapid development of science and technology and production technology, robotics technology has been continuously studied and improved, and the application field of robots has also expanded rapidly, demonstrating its superior control performance and adaptability to the working environment in all aspects. In some complex application scenarios, a single robot has certain limitations. At this time, the collaborative work of multiple robots can often reduce the difficulty of work and improve work efficiency; multiple robots collaborate to complete certain tasks, and often need to form an orderly formation, that is, a multi-robot formation. Multiple robots go from the initial disordered state to an orderly formation. In order to improve the efficiency of formation formation, it is necessary to design a reasonable formation formation process path planning algorithm.

[0003] A spherical robot is a general term for a robot system that has a motion mechanism, sensor, controller, etc. built into a spherical shell. Compared with traditional wheeled and tracked mobile robots, it has the characteristics of small size, flexible movement, easy posture adjustment, and strong environmental adaptability. The spherical robot described in this article has the ability to roll at high speed. A spherical robot in a high-speed rolling state is prone to slipping. Therefore, unlike conventional path planning, the path planning of a high-speed rolling spherical robot needs to consider the smoothness of the path, thereby improving the motion smoothness of the high-speed rolling spherical robot. Summary of the invention

[0004] In view of this, the present invention provides a path planning algorithm for a multi-spherical robot formation process based on an improved artificial potential field method.

[0005] The present invention provides a path planning algorithm for a multi-spherical robot formation process based on an improved artificial potential field method, comprising:

[0006] According to the position information, map information and target position of the spherical robot, the gravitational function F of the virtual force acting on the spherical robot at the target position Gi is obtained. goal_i (P i );

[0007] Based on the position information P of the spherical robot and the speed information V of the spherical robot R , obtain the repulsive field function U between the spherical robots robot (P i , P j ) and the repulsion function F robot (Pi, Pj);

[0008] According to the gravitational function Fgoal_i (Pi) and the repulsion function F robot (Pi, Pj), obtain the resultant force function F of the virtual resultant force on the spherical robot all (P i );

[0009] The gravitational function F of the virtual force acting on the spherical robot at the target position goal_i (P i )for:

[0010]

[0011] Where dΔ=-log2(d thg )+d thg ;

[0012] d(P i ,G i ) indicates robot R i With the target point G i The Euclidean distance between the two, Pi = (xi, yi) is the spherical robot R i The real-time location of G i =(x gi ,y gi ) is the position of the target point corresponding to the spherical robot Ri, (x i ,y i ) and (x gi ,y gi ) are all coordinates in the inertial Cartesian coordinate system relative to the ground, k goal is the position gain coefficient, d thg is the distance threshold between the robot and the target point;

[0013] The repulsive field function U between the spherical robots robot (P i , P j )for:

[0014]

[0015] Among them, P j For the spherical robot R j The real-time position of i , P j ) represents the Euclidean distance between two robots, d_th represents the distance threshold between two robots, V Ri For robot R i The velocity vector, V Rj For robot R j The velocity vector of krobot (V Ri , V Rj) is the repulsion gain function, and the repulsion gain function is expressed as follows:

[0016]

[0017] Among them, e ij For R i The center of the ball points to R j The unit vector of the sphere's center, θ ij For the spherical robot R i and spherical robot R j The relative speed between Ri -V Rj ) and e ij According to the repulsive field function U between the spherical robots robot (P i , P j ), and obtain the repulsive force function F between the spherical robots robot (P i , P j )for:

[0018]

[0019] The resultant force function F of the virtual resultant force on the spherical robot is all (P i )for:

[0020]

[0021] Among them, ∑F obs (P i ) is a spherical robot R i The sum of the virtual repulsive forces of the obstacles, ∑ j≠i F robot (P i , P j ) is a spherical robot R i The sum of the virtual repulsive forces of other spherical robots; spherical robot R i Virtual repulsion F of the obstacle obs (P i )for:

[0022]

[0023] Among them, X obs is the position of the obstacle, d(P i , X obs ) represents the Euclidean distance between the robot and the obstacle, d_safe is the range of the obstacle repulsion. When the Euclidean distance between the spherical robot and the obstacle is greater than this value, the obstacle will not repel the robot. obsRepresents the repulsion gain coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments are briefly introduced below.

[0025] Figure 1 It is a flow chart of a path planning algorithm for a multi-spherical robot formation process based on an improved artificial potential field method provided by an embodiment of the present invention;

[0026] Figure 2 is the map information used in the embodiment of the present invention;

[0027] Figure 3 It is the force diagram of the spherical robot Ri;

[0028] Figure 4 It is a schematic diagram of simulation results of an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a 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. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0030] The embodiment of the present invention takes four spherical robots forming a triangular formation as an example.

[0031] The embodiment of the present invention provides a multi-spherical robot formation process path based on an improved artificial potential field method

[0032] For planning algorithms, please refer to Figure 1 , which is a flow chart of a path planning algorithm for the formation process of a multi-spherical robot formation based on an improved artificial potential field method provided by an embodiment of the present invention. Figure 1 As shown in the figure, the algorithm first needs to provide the initial position information of each spherical robot, map information, and the target point position information of each spherical robot; then the virtual attraction from the target point, the virtual repulsion from other spherical robots, and the virtual repulsion from obstacles are calculated respectively, and then the virtual resultant force acting on each spherical robot is obtained; then, each spherical robot obtains the position it should reach next through the virtual resultant force it receives and moves towards that position; finally, the previous steps are repeated until each spherical robot reaches its target position, that is, the formation is completed.

[0033] Specifically, Figure 2 As shown, it is the map information used in the embodiment of the present invention; Figure 2 As shown, black areas represent obstacles and blank areas represent free space.

[0034] Specifically, Figure 3 As shown in, it is a schematic diagram of the force on the spherical robot Ri. Figure 3 As shown in the figure, the virtual forces on the spherical robot include the repulsive force from obstacles, the repulsive force from other spherical robots and the gravitational force from its target point; these repulsive forces and gravitational forces together constitute the virtual resultant force acting on the spherical robot Ri, and the virtual resultant force determines the position that the spherical robot Ri needs to reach next, and finally reaches its target position. In this process, due to the repulsive force between the spherical robot and obstacles and other spherical robots, it can be ensured that the spherical robot Ri does not collide with obstacles and other spherical robots. Similarly, in the process of multiple spherical robots moving from the initial position to forming the expected formation, all spherical robots can ensure that they reach their respective target positions without colliding with obstacles and other spherical robots.

[0035] In the embodiment of the present invention, the map size is 500x500, the initial positions of the three spherical robots are respectively: (120, 60), (160, 50), (80, 60), and the target point positions of the three spherical robots are respectively: (200, 480), (250, 450), (150, 450).

[0036] The final simulation results are as follows Figure 4 As shown. Figure 4 It can be seen that the three spherical robots each plan a safe, collision-free, and efficient path in the map from their initial position based on the virtual forces of obstacles, other robots, and their target points, and finally reach the corresponding target position to form the expected formation shape, verifying the effectiveness of the path planning algorithm for the multi-spherical robot formation formation process based on the improved artificial potential field method proposed in the present invention.

Claims

1. A path planning algorithm for the formation process of multi-spherical robots based on an improved artificial potential field method, characterized in that: The algorithm includes: obtaining the target position G according to the position information, map information and target position of the spherical robot i The gravitational function F of the virtual force acting on the spherical robot goal_i (P i ); Based on the position information P of the spherical robot and the speed information V of the spherical robot R , obtain the repulsive field function U between the spherical robots robot (P i , P j ) and the repulsion function F robot (P i , P j );According to the gravitational function F goal_i (P i ) and the repulsion function F robot (P i , P j ), and obtain the resultant force function F of the virtual resultant force on the spherical robot all (P i ); The gravitational function F of the virtual force acting on the spherical robot at the target position goal_i (P i )for: Among them, d Δ = -log2(d thg )+d thg , d(P i ,G i ) indicates robot R i With the target point G i The Euclidean distance between i =(x i ,y i ) is a spherical robot R i The real-time location of G i =(x gi ,y gi ) is a spherical robot R i The corresponding target point position, (x i ,y i ) and (x gi ,y gi ) are all coordinates in the inertial Cartesian coordinate system relative to the ground, k goal is the position gain coefficient, d thg is the distance threshold between the robot and the target point; The repulsive field function U between the spherical robots robot (P i , P j )for: Among them, P j For the spherical robot R j The real-time position of i , P j ) represents the Euclidean distance between two robots, d_th represents the distance threshold between two robots, V Ri For robot R i The velocity vector, V Rj For robot R j The velocity vector, k robot (V Ri , V Rj ) is the repulsion gain function, and the repulsion gain function is expressed as follows: Among them, e ij For R i The center of the ball points to R j The unit vector of the sphere's center, θ ij For the spherical robot R i and spherical robot R j The relative speed between Ri -V Rj ) and e ij According to the repulsive field function U between the spherical robots robot (P i , P j ), and obtain the repulsive force function F between the spherical robots robot (P i , P j )for: The resultant force function F of the virtual resultant force on the spherical robot all (P i )for: Among them, ∑F obs (P i ) is a spherical robot R i The sum of the virtual repulsive forces of the obstacles, ∑ j≠i F robot (P i , P j ) is a spherical robot R i The sum of the virtual repulsive forces of other spherical robots; spherical robot R i Virtual repulsion F of the obstacle obs (P i )for: Among them, X obs is the position of the obstacle, d(P i , X obs ) represents the Euclidean distance between the robot and the obstacle, d_safe is the range of the obstacle repulsion, k obs Represents the repulsion gain coefficient.

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