Omnidirectional Robot Group Cooperative Path Planning and Navigation Method, System and Storage Medium

Abstract

The present invention discloses an omnidirectional robot group collaborative path planning and navigation method, system and storage medium. Among them, the collaborative path planning and navigation method includes the following steps: S1. Collect data received by the master robot from its own sensors and construct a global planning trajectory; S2. Calculate the current actual distance between the master robot and the slave robot, and control the slave robot to maintain a preset collaborative spacing range from the master robot; S3. Drive the master robot and the slave robot to move synchronously according to the global planning trajectory; S4. Collect data received by the slave robot from its own sensors and locally optimize the path planning trajectory of the slave robot; S5. Repeat steps S1-S4 until the master robot reaches the target point. The present invention improves the processing efficiency of multi-robot coordinated control by locally optimizing the path planning trajectory, precisely controlling the paths of each slave robot, facilitating sequential passage through narrow space channels without collision.

Description

Technical Field

[0001] The present invention relates to the technical field of robot navigation control, and specifically to an omnidirectional robot group collaborative path planning navigation method, system, and storage medium. Background Technique

[0002] With the entry of artificial intelligence technology into the golden period of technological development, mobile robots integrating functions such as environmental perception, dynamic decision-making, and planning have been pushed to a new height in the development of many fields. Path planning is a process of inspecting the target structure and environment based on a robot equipped with a radar device, that is, calculating the driving path of a robot. Currently, researchers' research on robot path planning mainly focuses on single robots. In addition to single mobile robots, collaborative path planning of collaborative robots is also one of the current topics.

[0003] For example, the path planning method for multi-mobile robot collaboration disclosed in the application publication number CN117970928A. The multi-machine system adopted in the above solution can decouple complex tasks, adapt to the solution of complex tasks, and at the same time make the system have task flexibility; reduce the computing pressure of a single computer, thereby improving computing efficiency and having higher controllability, fault tolerance, and robustness.

[0004] However, the space mainly applied in the above solution is relatively broad. For narrow space channels, it is difficult to accurately control the paths of each robot so that they do not collide; in addition, in traditional robot control systems, task allocation usually adopts centralized and distributed task allocation algorithms. These two algorithms have various problems. For example, the centralized task allocation algorithm requires a large amount of computing resources to process task allocation. As the number of robots increases, the control difficulty increases; the distributed task allocation algorithm cannot globally optimize task allocation, and frequent communication between robots will cause network congestion or delay, affecting the timeliness of the system; path planning usually adopts the A* algorithm based on graph search, but this algorithm needs to calculate the path at all times in the face of a dynamic environment with obstacles, increasing the amount of calculation. Summary of the Invention

[0005] The purpose of the present invention is to provide an omnidirectional robot group collaborative path planning navigation method, system, and storage medium to solve the problems raised in the above background technique.

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

[0007] The omnidirectional robot group collaborative path planning navigation method includes the following steps:

[0008] S1. Collect the data received by the master robot from its own sensors and construct a global planning trajectory;

[0009] S2. Calculate the current actual distance between the master robot and the slave robot. If the current actual distance is less than the preset collaborative spacing range, drive the slave robot away from the master robot; if the current actual distance is greater than the preset collaborative spacing range, drive the slave robot closer to the master robot.

[0010] S3. Drive the master robot and the slave robot to move synchronously according to the global planned trajectory.

[0011] S4. Collect the data received by the slave robot from its own sensors, check and calculate the real-time distance between the slave robot and the detected obstacles. If the real-time distance is less than the set safety distance, drive the slave robot to move in a circular motion around the master robot with the master robot as the center to move away from the obstacles; otherwise, continue to drive the slave robot to run along the current planned trajectory.

[0012] S5. Repeat steps S1 - S4 until the master robot reaches the target point.

[0013] As a further solution of the present invention, both the master robot and the slave robot are four-wheel omnidirectional mobile robots. The moving parts of the four-wheel omnidirectional mobile robots adopt Mecanum wheels. The local velocity of the four-wheel omnidirectional mobile robot in the x-axis direction in the local reference system and the local velocity in the y-axis direction have the following related expressions:

[0014]

[0015] where ω1, ω2, ω3, and ω4 are the angular velocities of the motor shafts of the four-wheel omnidirectional mobile robot respectively, V1, V2, V3, and V4 are the velocities of the wheels of the four-wheel omnidirectional mobile robot respectively, L is the radius of the four-wheel omnidirectional mobile robot, r 轮 is the wheel radius, and W P is the angular velocity of the four-wheel omnidirectional mobile robot rotating around its own center;

[0016] According to the rotation angle θ between the global reference system (X, Y) and the local reference system (x, y), the global velocity of the four-wheel omnidirectional mobile robot in the X-axis direction the global velocity in the Y-axis direction the local velocity in the x-axis direction the local velocity in the y-axis direction have the following related expressions:

[0017]

[0018]

[0019] As a further solution of the present invention, the related expression of the angular velocity ω of the slave robot moving in a circular motion around the master robot in step S4 is:

[0020] V ax = V mx + ωD p sinδ

[0021] V ay = V my + ωD p cosδ;

[0022] Among them, V ax is the x-direction velocity vector required for the angular motion of the slave robot, V ay is the y-direction velocity vector required for the angular motion of the slave robot, V mx is the X-direction velocity vector of the master robot, V my is the Y-direction velocity vector of the master robot, δ is the angle between the master robot and the slave robot, and the preset cooperative distance between the master robot and the slave robot is D p ;

[0023] The related expression of the angular velocity direction of the slave robot moving in a circular motion around the master robot is:

[0024]

[0025] Among them, D t is the distance between the slave robot and the obstacle at the current moment, D t+1 is the distance between the slave robot and the obstacle at the next moment.

[0026] The omnidirectional robot group cooperative path planning and navigation system includes:

[0027] At least two numbered omnidirectional mobile robots, which are configured with a communication module and sensors, and the sensors are used to detect obstacle data around the omnidirectional mobile robots; communication data is transmitted between the omnidirectional mobile robots through the communication module;

[0028] The omnidirectional mobile robot with a later number takes the omnidirectional mobile robot with the previous number as its master robot, and so on;

[0029] The omnidirectional mobile robot is also configured with a global path planning module and / or a local path planning module. The global path planning module constructs a global planning trajectory according to the data received from its own sensors by the first-numbered omnidirectional mobile robot, and sends the global planning trajectory to the remaining omnidirectional mobile robots through the communication module. Each omnidirectional mobile robot performs cooperative motion according to the global planning trajectory and the preset cooperative distance range;

[0030] The local path planning module checks and calculates the real-time distance between the slave robot and the detected obstacles according to the data received by the slave robot from its own sensors. If the real-time distance is less than the set safety distance, it constructs the local planning trajectory of the slave robot and sends the local planning trajectory to the omnidirectional mobile robot with a later number. According to the local planning trajectory, the current slave robot moves in a circular motion around the master robot with the master robot as the center, away from the obstacle, and the omnidirectional mobile robot with a later number performs cooperative motion according to the latest received local planning trajectory and the preset cooperative spacing range; otherwise, the slave robot continues to run according to the current planning trajectory.

[0031] Each omnidirectional mobile robot executes the above-mentioned cooperative path planning and navigation method for the omnidirectional robot group.

[0032] A storage medium stores computer instructions, and when the computer instructions are executed by a processor, the above-mentioned cooperative path planning and navigation method is executed.

[0033] The cooperative control method for the omnidirectional robot group includes the following steps:

[0034] F1. Verify whether the current task of the omnidirectional mobile robot has been defined. If not, execute the DQN task allocation algorithm module for task allocation; use the omnidirectional mobile robot with the first number as the highest-level robot, and it allocates tasks to other omnidirectional mobile robots.

[0035] F2. After the current task of the omnidirectional mobile robot is defined, check whether there is a need to continue executing the current task; if there is a need to execute, run the navigation DQN algorithm module, execute the above-mentioned cooperative path planning and navigation method, and perform cooperative motion.

[0036] F3. At each step of executing the navigation DQN algorithm module, continuously evaluate its effectiveness. If there is no collision, the iterative process continues until each omnidirectional mobile robot completes the task and reaches the target point; if an omnidirectional mobile robot collides, the iterative task ends.

[0037] As a further solution of the present invention, the navigation reward mechanism of the navigation DQN algorithm module is designed as follows:

[0038]

[0039] where D t-1 represents the distance between the obstacle and the robot at time t - 1, and D t represents the distance between the obstacle and the robot at time t;

[0040]

[0041]

[0042] Among them, n robots represents the number of robots in the collaborative robot group, and P M represents the position of the master robot, and P iA represents the position of the slave robot.

[0043] As a further solution of the present invention, the task assignment reward mechanism of the DQN task assignment algorithm module is designed as follows:

[0044]

[0045] Among them, d max , d min and d sel respectively represent the distance between the farthest selectable robot and the highest-level robot, the distance between the nearest selectable robot and the highest-level robot, and the distance between the currently selected robot and the highest-level robot.

[0046] Among them,

[0047]

[0048]

[0049] Among them, n robots represents the number of robots in the collaborative robot group, D set represents the distance between the task target point and the master robot, and D i-set represents the distance between the i-th slave robot and the task target point.

[0050] A storage medium stores computer instructions, and when the computer instructions are executed by a processor, the above-mentioned cooperative control method is executed.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows: In terms of multi-robot task assignment and path planning, the present invention can automatically optimize the task assignment strategy in real time according to the robot state and task priority, avoiding the idle and waiting time caused by uneven task assignment in the traditional method, and at the same time can adapt to environmental changes and dynamically adjust task assignment; in a dynamic obstacle environment, the method and system of the present invention can re-plan the path in real time, reduce the unnecessary motion trajectory of the slave robot by locally optimizing the path planning trajectory, and can accurately control the paths of each slave robot, facilitating passing through narrow space channels in sequence without collision, thereby improving the processing efficiency of multi-robot coordinated control. Description of the Drawings

[0052] Figure 1 It is a schematic flow chart of the cooperative path planning and navigation method for an omnidirectional robot group;

[0053] Figure 2 This is a schematic diagram of the geometric configuration of the four-wheel omnidirectional mobile robot in the present invention;

[0054] Figure 3 This is a schematic diagram of the relative motion of the master robot and the slave robot in the present invention;

[0055] Figure 4 This is a schematic diagram of the cooperative motion of the master robot and the slave robot in the present invention;

[0056] Figure 5 This is a schematic diagram between the slave robot and the obstacle in the present invention;

[0057] Figure 6 This is a schematic diagram of the motion of the slave robot rotating clockwise around the master robot to avoid obstacles in the present invention;

[0058] Figure 7 This is a schematic diagram of the motion of the slave robot rotating counterclockwise around the master robot to avoid obstacles in the present invention;

[0059] Figure 8 This is a schematic diagram of the flow of the cooperative control method for the omnidirectional robot group in the present invention. Detailed implementation manners

[0060] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0061] Please refer to Figure 1 , the cooperative path planning and navigation method for the omnidirectional robot group, includes the following steps:

[0062] S1. Collect the data received by the master robot from its own sensors and construct a global planning trajectory; [[ID=!41]]

[0063] S2. Calculate the current actual distance between the master robot and the slave robot. If the current actual distance is less than the preset cooperative distance range, drive the slave robot away from the master robot; if the current actual distance is greater than the preset cooperative distance range, drive the slave robot closer to the master robot;

[0064] S3. Drive the master robot and the slave robot to move synchronously according to the global planning trajectory;

[0065] S4. Collect the data received by the slave robot from its own sensors, check and calculate the real-time distance between the slave robot and the detected obstacle. If the real-time distance is less than the set safety distance, drive the slave robot to move in a circular motion around the master robot with the master robot as the center to move away from the obstacle; otherwise, continue to drive the slave robot to run along the current planned trajectory;

[0066] S5. Repeat steps S1 - S4 until the master robot and the slave robot reach the target point.

[0067] The method of the present invention can re-plan the path of the slave robot in real time, reduce the unnecessary motion trajectory of the slave robot by locally optimizing the path planning trajectory, can accurately control the paths of each slave robot, facilitate passing through the narrow space channel in sequence without collision, thereby improving the processing efficiency of multi-robot coordinated control.

[0068] In the embodiment of the present invention, both the master robot and the slave robot are four-wheel omnidirectional mobile robots. The moving parts of the four-wheel omnidirectional mobile robots adopt Mecanum wheels, which ensure that the omnidirectional robot group can form motion configurations at multiple angles and directions in a limited space. Compared with differential drive wheeled robots, it is easier to achieve movement and steering.

[0069] In the present invention, the geometric configuration of the four-wheel omnidirectional mobile robot is as Figure 2 shown. The wheel angle of the four-wheel omnidirectional mobile robot is 90°. Each omnidirectional wheel and its motor shaft have the same axis of rotation; the speeds of each wheel are V1, V2, V3, and V4 respectively. According to these speeds, the driving directions of the unit vectors are defined as D1, D2, D3, and D4 respectively. For each wheel, the angular velocities of the motor shafts are ω1, ω2, ω3, and ω4 respectively, and counterclockwise rotation is regarded as positive rotation.

[0070] It is associated with a local reference frame (x, y), and the origin of its coordinates is determined by Figure 1 the center of mass of the omnidirectional robot in. The x-axis of the local reference frame points from the center of mass of the omnidirectional robot to the center of the fourth wheel, and the y-axis of the local reference frame points from the center of mass of the omnidirectional robot to the center of the third wheel. The rotation angle between the global reference frame (X, Y) and the local reference frame (x, y) is θ. The radius of the omnidirectional robot is set as L. The X-axis position vector of the center of mass of the omnidirectional robot in the global reference frame is defined as P ox and the Y-axis position vector of the center of mass of the omnidirectional robot in the global reference frame is defined as P oy . For the i-th wheel, in the global reference frame, r i is specified as the position vector from the center of mass of the omnidirectional robot to the i-th wheel. For the four-wheel omnidirectional mobile robot platform, is defined as the local speed value in the x-axis direction of the local reference frame, is defined as the local velocity value in the y-axis direction of the local reference frame, is defined as the global velocity value in the X-axis direction in the global reference frame, V y w is defined as the global velocity value in the Y-axis direction in the global reference frame.

[0071] The expression for the rotation transformation matrix R is:

[0072]

[0073] where γ is the rotation transformation angle;

[0074] Using the rotation transformation matrix given by formula (1), the position P of the i-th wheel relative to the center of mass in the local reference frame is obtained 0i , as shown in the following formula:

[0075]

[0076] From formula (2), the positions of each wheel relative to the center of mass in the local reference frame are specifically:

[0077]

[0078] The specific expression of the driving direction of the unit vector, that is, the driving direction of the i-th motor relative to the center of the omnidirectional robot in the local reference frame, is:

[0079]

[0080] Then the position vector r of the i-th wheel relative to the center of mass in the global reference frame i is:

[0081]

[0082] Taking the derivative of formula (5) gives:

[0083]

[0084] where x is the coordinate of the center of mass of the omnidirectional robot on the X-axis in the global reference frame, and y is the coordinate of the center of mass of the omnidirectional robot on the Y-axis in the global reference frame;

[0085] Therefore, the individual speed formula for each wheel of the four-wheel omnidirectional mobile robot in the global reference frame is obtained as:

[0086]

[0087] According to the local reference frame, when θ = 0, the speed conversion matrix of the four wheels is calculated as shown in formula (8):

[0088]

[0089] Among them, W P is the angular velocity of the four-wheel omnidirectional mobile robot rotating around its own center;

[0090] Based on formula (8), the inverse kinematic equation of the four-wheel omnidirectional mobile robot is:

[0091]

[0092]

[0093]

[0094]

[0095] According to the θ angle relationship, the global velocity of the four-wheel omnidirectional mobile robot in the X-axis direction The global velocity in the Y-axis direction The local velocity in the x-axis direction The local velocity in the y-axis direction Related expressions:

[0096]

[0097]

[0098] Among them, the linear velocity conversion adopts V = ω·r 轮 , where r 轮 is the wheel radius, and the expression for the angular velocity to be transmitted to each motor shaft is:

[0099]

[0100] Among them, ω1, ω2, ω3, and ω4 are the angular velocities of the respective motor shafts of the four-wheel omnidirectional mobile robot, V1, V2, V3, and V4 are the speeds of the respective wheels of the four-wheel omnidirectional mobile robot, L is the radius of the four-wheel omnidirectional mobile robot, r 轮 is the wheel radius, W P is the angular velocity of the four-wheel omnidirectional mobile robot rotating around its own center;

[0101] In the present invention, the preset cooperation distance between the master robot and the slave robot is D p , and the cooperation distance error is β. Then the preset cooperation distance range between the master robot and the slave robot is D p ±β, and the motion state of the slave robot changes according to the change of the cooperation distance D p . For example Figure 3As shown, when the master robot is fixed in the X-Y coordinate system and remains stationary, and only the angular velocity is applied to the slave robot around the centroid of the master robot, the slave robot will perform angular motion around the master robot with a cooperative spacing D p as the radius.

[0102] The velocity vector required for the angular motion of the slave robot is V0 = ω·D p , and at the same time, the decomposed vectors on the X-Y coordinate system are: V ax = V0 cosδ and V ay = V0 sinδ.

[0103] The position angle δ between the master robot and the slave robot is obtained from Equation (16) as δ:

[0104]

[0105] Therefore, as Figure 4 shown, when the master robot is dynamically running, the expression related to the angular velocity ω of the slave robot moving in a circular motion around the master robot as the center in step S4 is:

[0106] V ax = V mx + ωD p sinδ

[0107] V ay = V my + ωD p cosδ (17);

[0108] Among them, V ax is the X-direction velocity vector required for the angular motion of the slave robot, V ay is the Y-direction velocity vector required for the angular motion of the slave robot, V mx is the X-direction velocity vector of the master robot, V my is the Y-direction velocity vector of the master robot, and δ is the angle between the master robot and the slave robot;

[0109] The trajectory planning trajectory point array of the master robot from the starting point to the target point is as shown in Formulas (19) and (20):

[0110] p i , i ∈ [0, 1, 2,..., n], p ≡ (p0, p1, p2,....p n ), p i = (x i , y i ) (18);

[0111] Among them, p iEach point in the planned trajectory is represented as, and p represents the trajectory curve formed by each point in the planned trajectory;

[0112] path M ={(x0,y0),(x1,y1),...,(x i ,y i )} (19);

[0113] Among them, path M represents the trajectory curve planned by the master robot;

[0114] The trajectory planning trajectory point array of the slave robot is as shown in the formula:

[0115] path Aj ={(x0,y0),(x1,y1),...,(x i ,y i ),}, j ∈ [0,1,2,...,n] (20);

[0116] Among them, path Aj represents the trajectory curve planned by the j-th slave robot.

[0117] During the cooperative movement, as Figure 5 shown, the slave robot always follows the master robot at a cooperative spacing. At the same time, in its local path planning module, the slave robot takes its own centroid as the center and scans the range with a radius of H to check for possible obstacles; the position of the slave robot is (x si , y si ), and each trajectory point in its planned trajectory is (x i , y i ). The path length between each trajectory point and the centroid of the slave robot is obtained through the following formula:

[0118]

[0119]

[0120] According to formula (22), each trajectory point with a path length greater than H is deleted, and each trajectory point with a path length less than or equal to H is retained. In this way, the local planned trajectory of the slave robot is restricted within the sensor scanning range of the slave robot.

[0121] When the slave robot identifies an obstacle through a laser sensor and calculates the real-time distance between its own position and each obstacle according to formula (23), if the real-time distance is less than the set safety distance D0, while maintaining the cooperative spacing D between the slave robot and the master robot pOn the premise of this, recalculate the angular velocity ω movement direction from the robot dynamically, so as to control the slave robot to move away from obstacles and avoid collisions with them.

[0122]

[0123] Among them, (x Di , y Di ) represents the coordinate of the obstacle surface point cloud data, and (x si , y si ) represents the real-time position coordinate of the slave robot;

[0124] In order to determine the angular velocity ω movement direction of the slave robot, it is necessary to judge the relative position of the obstacle. According to the relative position, determine the angular velocity direction applied to the slave robot. The relevant expression of the angular velocity direction of the slave robot moving in a circular motion around the centroid of the master robot with the centroid of the master robot as the center is:

[0125]

[0126] Among them, D t is the distance between the slave robot and the obstacle at the current moment, and D t+1 is the distance between the slave robot and the obstacle at the next moment.

[0127] As Figure 6 shown, during the collaborative movement of the slave robot and the master robot, the slave robot is located at the lower right of the master robot, and the obstacle is on the movement trajectory direction above the slave robot. When the real-time distance between the slave robot's own position and each obstacle is less than the set safety distance D0, on the premise that the slave robot and the master robot maintain the collaborative distance D p , the slave robot moves in a clockwise circular motion around the master robot to avoid obstacles.

[0128] As Figure 7 shown, during the collaborative movement of the slave robot and the master robot, the slave robot is located at the lower left of the master robot, and the obstacle is on the movement trajectory direction above the slave robot. When the real-time distance between the slave robot's own position and each obstacle is less than the set safety distance D0, on the premise that the slave robot and the master robot maintain the collaborative distance D p , the slave robot moves in a counterclockwise circular motion around the master robot to avoid obstacles.

[0129] The omnidirectional robot group collaborative path planning and navigation system includes:

[0130] At least two numbered omnidirectional mobile robots, which are configured with a communication module and sensors. The sensors are used to detect the obstacle data around the omnidirectional mobile robots; Communication data is transmitted between each omnidirectional mobile robot through the communication module;

[0131] The omnidirectional mobile robot with a later number takes the omnidirectional mobile robot with the previous number as its master robot, and so on;

[0132] The omnidirectional mobile robot is also equipped with a global path planning module and / or a local path planning module. The global path planning module constructs a global planned trajectory based on the data received from its own sensors by the omnidirectional mobile robot with the first number, and sends the global planned trajectory to the other omnidirectional mobile robots through the communication module. Each omnidirectional mobile robot performs collaborative movement according to the global planned trajectory and the preset collaborative spacing range;

[0133] The local path planning module checks and calculates the real-time distance between the slave robot and the detected obstacles according to the data received from the sensors of the slave robot. If the real-time distance is less than the set safety distance, it constructs the local planned trajectory of the slave robot and sends the local planned trajectory to the omnidirectional mobile robot with a later number. According to the local planned trajectory, the current slave robot makes a circular motion around the master robot with the master robot as the center to move away from the obstacle. The omnidirectional mobile robot with a later number performs collaborative movement according to the latest received local planned trajectory and the preset collaborative spacing range; otherwise, the slave robot continues to run according to the current planned trajectory;

[0134] Each omnidirectional mobile robot executes the above-mentioned collaborative path planning and navigation method for the omnidirectional robot group to perform collaborative movement.

[0135] A storage medium stores computer instructions, which when executed by a processor, execute the above-mentioned collaborative path planning and navigation method.

[0136] For the collaborative control method of the omnidirectional robot group, please refer to Figure 8 , including the following steps:

[0137] F1. Verify whether the current task of the omnidirectional mobile robot has been defined. If not, execute the DQN task allocation algorithm module for task allocation; among them, the omnidirectional mobile robot with the first number is used as the highest-level robot, and it allocates tasks to other omnidirectional mobile robots;

[0138] F2. After the current task of the omnidirectional mobile robot is defined, check whether there is a need to continue executing the current task to prevent other omnidirectional mobile robots in the group from being executing or having completed; if there is a need to execute, run the navigation DQN algorithm module, execute the above-mentioned collaborative path planning and navigation method for the omnidirectional robot group, and perform collaborative movement;

[0139] F3. At each step of running the navigation DQN algorithm module, its effectiveness is continuously evaluated. If no collision occurs, the iterative process continues until each omnidirectional mobile robot completes the task and reaches the target point. If an omnidirectional mobile robot collides, the iterative task ends.

[0140] Distributed DRL (Deep Reinforcement Learning) algorithms usually adopt adaptive reward mechanisms, leaderless environment control methods, and synchronous learning methods, and perform well in dealing with large-scale and high-complexity decision-making problems. On this basis, the present invention integrates the task allocation problem and the navigation problem into the DRL framework. To solve these two problems simultaneously, a DQN (combining Q-learning and deep neural networks) algorithm module for navigation and task allocation is managed through the DRL algorithm framework, and the part of it communicating with the agent and the environment is deleted. This algorithm runs inside each robot and interacts with the environment.

[0141] As a further solution of the present invention, the navigation reward mechanism in this embodiment focuses on four different situations: the master robot reaches the target, the slave robot with a later number reaches the target, a collision occurs, and the robot pauses. The main purpose of navigation is to reach the target without collision. Therefore, the navigation reward mechanism of the navigation DQN algorithm module is designed as follows:

[0142]

[0143] Among them, D t-1 represents the distance between the obstacle and the slave robot at time t - 1, and D t represents the distance between the obstacle and the slave robot at time t;

[0144] Among them,

[0145]

[0146]

[0147] Among them, n robots represents the number of robots in the cooperative robot group, P M represents the position of the master robot, and P iA represents the position of the slave robot.

[0148] In the navigation task, the navigation reward mechanism can be designed according to the distance of the robot approaching the target. The closer to the target, the higher the reward. A reasonable reward design can help the robot reach the target point faster and safer, and enable the robot group to complete the task faster and better.

[0149] As a further solution of the present invention, the task assignment reward mechanism in this embodiment mainly has two cases: selecting an idle target and selecting a target to be completed first. The task assignment reward mechanism of the DQN task assignment algorithm module is designed as follows:

[0150]

[0151] Among them, d max 、d min and d sel respectively represent the distance between the farthest selectable robot and the highest-level robot, the distance between the nearest selectable robot and the highest-level robot, and the distance between the currently selected robot and the highest-level robot;

[0152] Among them,

[0153]

[0154]

[0155] Among them, n robots represents the number of robots in the cooperative robot group, D set represents the distance between the task target point and the main robot, and D i-set represents the distance between the i-th slave robot and the task target point.

[0156] By means of a reasonable task assignment reward mechanism, it helps the robot group to clarify the task objectives. In the complex task assignment process, the reward mechanism can also be designed for multi-objective optimization, designed according to the distance of the robot approaching the target, and tasks are preferentially assigned to the robot closest to the target, improving the task completion efficiency and reducing unnecessary energy consumption of the robot group.

[0157] The method of the present invention uses the first numbered omnidirectional mobile robot as the highest-level robot, which distributes tasks to other omnidirectional mobile robots through the DQN task assignment algorithm module. Through the design of a reasonable task assignment reward mechanism, it can automatically optimize the task assignment strategy in real time according to the state and task priority of the robot, avoiding the idle and waiting time caused by uneven task assignment in the traditional method, and at the same time being able to adapt to environmental changes and dynamically adjust the task assignment.

[0158] Through the navigation DQN algorithm module, it can not only ensure the safe operation of the robot by preventing collisions, but also quickly eliminate invalid paths through real-time collision feedback, accelerating the training speed, ensuring that in a dynamic environment, the system can execute tasks more flexibly and reliably, maintaining high-efficiency cooperation.

[0159] A storage medium stores computer instructions, and when the computer instructions are executed by a processor, the above-mentioned cooperative control method is executed.

[0160] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. Omnidirectional robot group collaborative path planning and navigation method, characterized in that, It includes the following steps: S1. Collect the data received by the master robot from its own sensors and construct a global planned trajectory; S2. Calculate the current actual distance between the master robot and the slave robot. If the current actual distance is less than the preset cooperative spacing range, drive the slave robot away from the master robot; if the current actual distance is greater than the preset cooperative spacing range, drive the slave robot closer to the master robot; S3. Drive the master robot and the slave robot to move synchronously according to the global planned trajectory; S4. Collect the data received by the slave robot from its own sensors, check and calculate the real-time distance between the slave robot and the detected obstacles. If the real-time distance is less than the set safety distance, drive the slave robot to move in a circular motion around the master robot with the master robot as the center to move away from the obstacles; otherwise, continue to drive the slave robot to run along the current planned trajectory; S5. Repeat steps S1 - S4 until the master robot reaches the target point.

2. The omnidirectional robot group collaborative path planning and navigation method according to claim 1, characterized in that Both the master robot and the slave robot are four-wheel omnidirectional mobile robots. The moving parts of the four-wheel omnidirectional mobile robot adopt Mecanum wheels. The local velocity in the x-axis direction and the local velocity in the y-axis direction of the four-wheel omnidirectional mobile robot in the local reference frame and the relevant expressions of the local velocity in the y-axis direction are as follows: Among them, ω1, ω2, ω3, and ω4 are the angular velocities of the motor shafts of the four-wheel omnidirectional mobile robot respectively, V1, V2, V3, and V4 are the speeds of the wheels of the four-wheel omnidirectional mobile robot respectively, L is the radius of the four-wheel omnidirectional mobile robot, r 轮 is the wheel radius, W P is the angular velocity of the four-wheel omnidirectional mobile robot rotating around its own center; According to the rotation angle θ between the global reference system (X, Y) and the local reference system (x, y), the global velocity of the four-wheel omnidirectional mobile robot in the X-axis direction The global velocity in the Y-axis direction The local velocity in the x-axis direction The local velocity in the y-axis direction Related expressions are as follows:

3. The omnidirectional robot group collaborative path planning and navigation method according to claim 1, wherein In step S4, the relevant expression of the angular velocity ω of the slave robot moving in a circular motion around the master robot with the master robot as the center is: Among them, V ax is the x-direction velocity vector required for the angular motion of the slave robot, V ay is the y-direction velocity vector required for the angular motion of the slave robot, V mx is the X-direction velocity vector of the master robot, V my is the Y-direction velocity vector of the master robot, δ is the angle between the master robot and the slave robot, and the preset cooperative distance between the master robot and the slave robot is D p ; The relevant expression of the direction of the angular velocity of the slave robot moving in a circular motion around the master robot with the master robot as the center is: Among them, D t is the distance between the robot and the obstacle at the current moment, and D t+1 is the distance between the robot and the obstacle at the next moment.

4. Omnidirectional robot group collaborative path planning and navigation system, characterized in that, It includes: At least two numbered omnidirectional mobile robots, which are configured with a communication module and sensors. The sensors are used to detect the obstacle data around the omnidirectional mobile robots; communication data is transmitted between the omnidirectional mobile robots through the communication module; The omnidirectional mobile robot with a later number takes the omnidirectional mobile robot with the previous number as its own master robot, and so on; The omnidirectional mobile robot is also configured with a global path planning module and / or a local path planning module. The global path planning module constructs a global planned trajectory according to the data received by the first-numbered omnidirectional mobile robot from its own sensors, and sends the global planned trajectory to the rest of the omnidirectional mobile robots through the communication module. Each omnidirectional mobile robot performs cooperative motion according to the global planned trajectory and the preset cooperative spacing range; The local path planning module checks and calculates the real-time distance between the slave robot and the detected obstacles according to the data received by the slave robot from its own sensors. If the real-time distance is less than the set safety distance, it constructs the local planned trajectory of the slave robot and sends the local planned trajectory to the omnidirectional mobile robot with a later number. According to the local planned trajectory, the current slave robot moves in a circular motion around the master robot with the master robot as the center to move away from the obstacles, and the omnidirectional mobile robot with a later number performs cooperative motion according to the latest received local planned trajectory and the preset cooperative spacing range; otherwise, the slave robot continues to run along the current planned trajectory; Each omnidirectional mobile robot executes the cooperative path planning and navigation method for the omnidirectional robot group described in any one of claims 1 - 3.

5. A storage medium, characterized in that, Stored with computer instructions, when the computer instructions are executed by a processor, the cooperative path planning and navigation method described in any one of claims 1 - 3 is executed.

6. Omnidirectional robot group cooperative control method, characterized in that It includes the following steps: F1. Verify whether the current task of the omnidirectional mobile robot has been defined. If not, execute the DQN task allocation algorithm module for task allocation; use the omnidirectional mobile robot with the first number as the highest-level robot, and let it allocate tasks to other omnidirectional mobile robots. F2. After the current task of the omnidirectional mobile robot is defined, check whether there is a need to continue executing the current task; if there is a need to execute, run the navigation DQN algorithm module, execute the collaborative path planning and navigation method described in any one of claims 1-3, and perform collaborative movement. F3. At each step of executing the navigation DQN algorithm module, continuously evaluate its effectiveness. If no collision occurs, the iterative process continues until each omnidirectional mobile robot completes the task and reaches the target point; if an omnidirectional mobile robot collides, the iterative task ends.

7. The omnidirectional robot group collaborative control method according to claim 6, characterized in that The navigation reward mechanism of the navigation DQN algorithm module is designed as follows: Among them, D t-1 represents the distance between the obstacle and the robot at time t-1, and D t represents the distance between the obstacle and the robot at time t; Among them, n robots represents the number of robots in the collaborative robot group, P M represents the position of the master robot, P iA represents the position of the slave robot.

8. The omnidirectional robot group collaborative control method according to claim 7, wherein The task allocation reward mechanism of the DQN task allocation algorithm module is designed as follows: where d max , d min and d sel respectively represent the distance between the farthest selectable robot and the highest-level robot, the distance between the nearest selectable robot and the highest-level robot, and the distance between the currently selected robot and the highest-level robot; Wherein, Among them, n robots represents the number of robots in the collaborative robot group, D set represents the distance between the task target point and the master robot, D i-set represents the distance between the i-th slave robot and the task target point.

9. A storage medium, characterized in that, It stores computer instructions, and when the computer instructions are executed by a processor, it executes the collaborative control method described in any one of claims 6-8.

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