A Robot Path Planning Method and System Based on Avoidance Strategy

Abstract

The present invention relates to the technical field of path planning, and discloses a robot path planning method and system based on an avoidance strategy. A robot path planning method based on an avoidance strategy includes the following steps: A scheduling system generates a movement route for a robot; the scheduling system calculates whether the sum of the lengths of the road segments occupied by the current robot is less than planDist. If it is less, it determines whether the condition is met. If the condition is met, the robot is given the right of way; after the robot obtains the right of way, it occupies the next road segment and the end point of the next road segment, and travels towards the end point of the next road segment. When the robot has traveled a specified distance on the road segment, the starting point of the road segment is released; when the robot reaches the end point of the road segment, the road segment is released; each robot repeats the above steps until all robots reach the end point of the task. The present invention improves the overall order delivery efficiency by reducing the possibility of deadlocks occurring, quickly releasing deadlocks, and speed adjustment strategies.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and more specifically, to a robot path planning method and system based on an avoidance strategy. Background Art

[0002] In automated warehousing and manufacturing scenarios, multiple robots are often required to work together to complete material handling tasks. In order for the robots to complete tasks efficiently, safely, and without collision, the robot's motion path needs to be reasonably planned and scheduled. When multiple robots are assigned to carry goods from the pickup point to the delivery point in a limited space, the exact location of the robots cannot be confirmed in the case of poor network conditions.

[0003] When the network is good, robots that may collide need to wait for execution commands before executing them. This waiting process increases the time consumption of the entire task.

[0004] Since waybills are unpredictable, the execution efficiency of different waybill strategies is also different. Summary of the invention

[0005] The present invention provides a robot path planning method and system based on an avoidance strategy, which solves the technical problems in the related art such as poor network, inability to confirm the accurate position of the robot, increased possibility of deadlock, difficulty in releasing deadlock and low execution efficiency.

[0006] The present invention provides a robot path planning method based on an avoidance strategy, comprising the following steps:

[0007] Step 100, the scheduling system generates a movement route according to the current station of the robot and the task target station;

[0008] Step 200, the dispatching system calculates whether the sum of the lengths of the sections currently occupied by the robot is less than planDist based on the generated motion route. If so, it determines whether steps 201-204 are satisfied, and grants the robot corresponding access rights based on whether steps 201-204 are satisfied.

[0009] Step 201, perform deadlock detection to determine whether the current robot will be deadlocked with other robots when driving to the end of the next road segment; if not, proceed to step 202; if it occurs and can be resolved, generate a waiting instruction for the current station; if it occurs and cannot be resolved, adopt an avoidance strategy;

[0010] Step 202, the scheduling system determines whether the next section and the end point of the next section are occupied by other robots; if the next section or the end point of the next section is occupied by other robots, the scheduling system instructs the robot to wait at the current station; if the robot has occupied the next section and the end point of the next section, the scheduling system instructs the robot to travel to the end point of the next section; if neither the next section nor the end point of the next section is occupied, then proceed to Step 203;

[0011] Step 203, the scheduling system uses a collision detection method to determine whether the robot will collide with other robots during the process of traveling to the end point of the next section according to the length, width and traveling direction angle of the robot; if there will be a collision, the scheduling system adopts a speed adjustment strategy for the robot; if there will be no collision, then proceed to Step 204;

[0012] Step 204, determine whether the next section and the end point of the next section are in the exclusive area; if there are other robots in the exclusive area, the scheduling system instructs the robot to wait at the current station; if there are no other robots in the exclusive area, then the robot obtains the right of way;

[0013] Step 300, when the robot obtains the right of way, the robot occupies the next section and the end point of the next section, and the scheduling system instructs the robot to travel to the end point of the next section. When the robot has traveled a specified distance on the section, the starting point of the section is released, and this specified distance is set to the maximum length of the robot plus the safety margin and the positioning error; when the robot travels to the end point of the section, the section is released;

[0014] Step 400, each robot repeats Steps 100 - 300 until all robots reach the end point of the task.

[0015] In a preferred embodiment, the deadlock detection method is as follows:

[0016] If two robots are about to deadlock, the judgment method is that the remaining path of Robot One is about to pass through the occupied station of Robot Two or the associated station of the occupied station, and at the same time the remaining path of Robot Two is also about to pass through the next station of Robot One or its associated station, then Robot One needs to stop at the current station and wait for Robot Two to pass through the next station of Robot One or its associated station;

[0017] The associated station of a certain station means that if there is a robot on this station, there cannot be other robots on its associated station at the same time, otherwise there will be a collision, and these stations are called the associated stations of this station; the remaining path of the robot refers to the path from the current station to the current task end point of the robot, excluding the path that the robot has already traveled.

[0018] In a preferred embodiment, the avoidance strategy is as follows:

[0019] If there are fixed avoidance points in the scenario, select a robot that has deadlocked and search for the nearest avoidance point that is not occupied by other robots and will not deadlock with other robots during the process of reaching this avoidance point. If an avoidance point that meets this condition is found, occupy this avoidance point and update the path to this avoidance point; if not found, the path will be updated by choosing the one with the minimum path update cost in the case of deadlock; if there are no fixed avoidance points in the scenario, select an idle storage point or an idle docking point as a temporary avoidance point; after executing the above avoidance strategy, if the deadlock is still not resolved, increment the robots that need to execute the avoidance strategy one by one and repeat the above avoidance strategy until the deadlock is resolved.

[0020] In a preferred embodiment, the collision detection method is as follows: Based on the two rectangular bounding boxes formed by the lengths, widths, driving direction angles, safety margins, and positioning errors of two robots, determine whether the two bounding boxes intersect. If they intersect, the two robots will collide; otherwise, they will not collide. The default value of the safety margin is 300 mm, and the default value of the positioning error is 20 mm.

[0021] In a preferred embodiment, the scheduling system has an input parameter planDist, which is the distance that the scheduling system plans in advance for the robot to walk each time, and the default value is 3 meters. The scheduling system calculates whether the sum of the lengths of the occupied sections is less than planDist. If it is less than planDist, continue to judge whether the robot can reach the next section and the end of the next section according to steps 201 - 204. The sections occupied by the robot, that is, the sections assigned to the robot by the scheduling system, are the routes that the robot must travel. If it is greater than planDist, the judgment of the current robot in this round of planning ends, and the next robot is continued to be planned until the judgment of all robots in this round of planning ends.

[0022] In a preferred embodiment, in the mutually exclusive area, there can be at most one robot.

[0023] In a preferred embodiment, the speed adjustment strategy is as follows:

[0024] Step 1, obtain the state information of the current robot and other robots in the scenario at the current time step.

[0025] Step 2, construct a directed graph G(V, E) for the state information of the multiple robots obtained at the current time step. Each robot is a node, and the edge represents the influence relationship of each robot. The node feature is the state information feature of the robot.

[0026] Step 3, construct a speed adjustment model.

[0027] Step 4, the model outputs the adjustment amount of the current robot speed.

[0028] In a preferred embodiment, the loss function of the speed adjustment model is:

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] : Safety loss term;

[0034] : Smoothness loss term;

[0035] : Efficiency loss term;

[0036] : Safety distance threshold;

[0037] : Euclidean distance between the i-th robot and the j-th robot;

[0038] : New acceleration of the i-th robot after adjustment;

[0039] : New speed of the i-th robot after adjustment;

[0040] : Desired speed;

[0041] 、 、 : First, second, and third weight coefficients;

[0042] : Total reward function.

[0043] The present invention also provides a robot path planning system based on an avoidance strategy, which is used to execute the above-mentioned robot path planning method based on an avoidance strategy.

[0044] The beneficial effects of the present invention are as follows: the present invention implements an efficient waybill strategy, and during the waybill process, the robot occupies not a spatial position in the scheduling system, but a route, a group of mutually exclusive groups, and a detour area, thereby reducing the possibility of deadlock. Even if deadlock occurs, the deadlock can be resolved through an avoidance strategy, and a speed adjustment strategy is performed when a collision is about to occur, thereby improving the overall waybill efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of a robot path planning method based on an avoidance strategy of the present invention;

[0046] Figure 2 It is a flow chart for judging traffic conditions in a robot path planning method based on an avoidance strategy of the present invention. DETAILED DESCRIPTION

[0047] The subject matter described herein will now be discussed with reference to example implementations. It should be understood that the discussion of these implementations is only to enable those skilled in the art to better understand and implement the subject matter described herein, and the functions and arrangements of the elements discussed may be changed without departing from the scope of protection of the present specification. Various examples may omit, replace, or add various processes or components as needed. In addition, the features described in some examples may also be combined in other examples.

[0048] At least one embodiment of the present invention discloses a robot path planning method based on an avoidance strategy, such as Figure 1 As shown, the following steps are included:

[0049] Step 100, the scheduling system generates a movement route according to the current station of the robot and the task target station;

[0050] In one embodiment of the present invention, the dispatching system is a comprehensive system that integrates the back-end Core (development), front-end software (including implementation tools RoboShop Pro and RDS (development), etc.), simulation robots, and simulation equipment. It realizes the communication connection between various components through multiple protocols such as HTTP, TCP, and ModbusTCP. It can reasonably dispatch multiple robots to complete the task of transporting goods from the pickup point to the delivery point in a limited space according to the orders issued by users or WMS (Warehouse Management System), and has complex traffic control, task management, equipment monitoring and operation functions, aiming to improve logistics transportation efficiency, reduce implementation costs, and ensure the efficient and stable operation of the entire logistics operation process.

[0051] Step 200, the dispatching system calculates whether the sum of the lengths of the sections currently occupied by the robot is less than planDist based on the generated motion route. If so, it determines whether steps 201-204 are satisfied, and grants the robot corresponding access rights based on whether steps 201-204 are satisfied.

[0052] The steps of determining whether steps 201-204 are satisfied are as follows: Figure 2 As shown, including:

[0053] Step 201, perform deadlock detection to determine whether the current robot will be deadlocked with other robots when driving to the end of the next road segment; if not, proceed to step 202; if it occurs and can be resolved, generate a waiting instruction for the current station; if it occurs and cannot be resolved, adopt an avoidance strategy;

[0054] In one embodiment of the present invention, the deadlock detection method is as follows:

[0055] If the remaining path of Robot No. 1 is about to pass through the occupied site of Robot No. 2 or the associated site of the occupied site, and the remaining path of Robot No. 2 is also about to pass through the next site of Robot No. 1 or its associated site, it is judged that a deadlock is about to occur. The method to be adopted is: Robot No. 1 needs to stop at the current site and wait for Robot No. 2 to pass through the next site of Robot No. 1 or its associated site.

[0056] In one embodiment of the present invention, if two robots have deadlocked, the robot with the smallest updated path cost is selected to go to the avoidance point, that is, the robot that is closer to the nearest avoidance point and does not deadlock with other robots.

[0057] In one embodiment of the present invention, if a loop deadlock occurs among three robots, the judgment method is that robot No. 1 is about to pass through the occupied site of robot No. 2 or its associated site, and robot No. 2 is about to pass through the occupied site of robot No. 3 or its associated site, and robot No. 3 or No. 2 is also about to pass through the current site of robot No. 1 or its associated site, and a closed loop needs to be formed, that is, the loop occupies each other, before it can be judged as a loop deadlock; if a loop deadlock occurs among more than three robots, the judgment method is similar. When a loop deadlock occurs, firstly, all robots in the deadlock loop need to be detected according to the above method, and then the robot with the smallest path update cost is selected to update the path to the nearest avoidance point. If a robot deadlocks with other robots in the process of going to the avoidance point, the robot with the smallest path update cost will delete the original avoidance point plan, re-update the path to the new nearest avoidance point or restore the original path.

[0058] It should be noted that the associated sites of a certain site refer to that if there is a robot on this site, there cannot be other robots on its associated sites at the same time, otherwise collisions will occur. These sites are called the associated sites of this site. The remaining path of the robot refers to the path from the current site to the end point of the current task, excluding the path that the robot has already traveled.

[0059] In an embodiment of the present invention, the avoidance strategy is as follows:

[0060] If there are fixed avoidance points in the scenario, select a deadlocked robot and search for the nearest avoidance point that is not occupied by other robots and will not deadlock with other robots during the process of reaching this avoidance point. If an avoidance point that meets this condition is found, occupy this avoidance point and update the path to this avoidance point; if not found, the path will be updated by choosing the one with the minimum updated path cost in the case of deadlock; if there are no fixed avoidance points in the scenario, select an idle library site or an idle docking point as a temporary avoidance point; after executing the above avoidance strategy, if the deadlock is still not released, add the robots that need to execute the avoidance strategy one by one and repeat the above avoidance strategy until the deadlock is released;

[0061] Updating the path with the minimum path cost means that the robot selects the path with the highest comprehensive score when planning the path; the comprehensive score includes a short path, many avoidance points, and no deadlock with other robots when updating the path.

[0062] Step 202, the scheduling system determines whether the next section and the end point of the next section are occupied by other robots; if the next section or the end point of the next section is occupied by other robots, the scheduling system instructs the robot to wait at the current site; if the robot has occupied the next section and the end point of the next section, the scheduling system instructs the robot to move forward to the end point of the next section; if neither the next section nor the end point of the next section is occupied, then judge step 203;

[0063] Step 203, the scheduling system uses a collision detection method to determine whether the robot will collide with other robots during the process of driving to the end point of the next section according to the length, width and driving direction angle of the robot; if there will be a collision, the scheduling system adopts a speed adjustment strategy for the robot; if there will be no collision, then judge step 204;

[0064] In an embodiment of the present invention, the collision detection method is: according to the rectangular bounding boxes formed by the length, width, driving direction angle, safety margin and positioning error of the robot, judge whether the two bounding boxes intersect. If they intersect, the two robots will collide, otherwise they will not collide; the default value of the safety margin is 300mm, and the default value of the positioning error is 20mm.

[0065] In an embodiment of the present invention, the speed adjustment strategy is as follows:

[0066] Step 1: Obtain the state information of the current robot and other robots in the scene at the current time step;

[0067] The state information of the robot includes: the current speed, acceleration, driving direction angle, position coordinates, length, and width of the robot;

[0068] Step 2: Construct a directed graph G(V, E) for the state information of multiple robots obtained at the current time step. Each robot is a node, the edge represents the influence relationship of each robot, and the node feature is the state information feature of the robot;

[0069] Step 3: Construct a speed adjustment model;

[0070] In an embodiment of the present invention, MLP, GRU, and GNN are applied to execute Step 3, and the specific formulas are as follows:

[0071] Initialization of node features:

[0072] ;

[0073] : The initialized node feature of the i-th robot;

[0074] : Multilayer perceptron;

[0075] : The node feature of the i-th robot;

[0076] Edge feature between the i-th robot and the j-th robot: ;

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] 、 : The position coordinates of the i-th and j-th robots in the two-dimensional plane;

[0082] 、 : The speeds of the i-th and j-th robots;

[0083] 、 : The acceleration of the i-th and j-th robots;

[0084] 、 : The direction angle of travel of the i-th and j-th robots;

[0085] : The Euclidean distance between the i-th and j-th robots;

[0086] : The speed difference between the i-th and j-th robots;

[0087] : The acceleration difference between the i-th and j-th robots;

[0088] : The minimum angle difference between the i-th and j-th robots;

[0089] : The edge feature between the i-th and j-th robots;

[0090] Edge attention calculation:

[0091] ;

[0092] : The attention weight coefficient, indicating the influence degree of node j on node i;

[0093] : The hidden state of node i in the k-th layer;

[0094] : The hidden state of node j in the k-th layer;

[0095] : The hidden state of node k in the k-th layer;

[0096] : The edge feature between the i-th and j-th robots;

[0097] : The edge feature between the i-th and k-th robots;

[0098] : The vector concatenation operator;

[0099] : The set of neighbor nodes of node i;

[0100] : The learnable attention weight matrix;

[0101] : Activation function;

[0102] Message passing:

[0103] ;

[0104] : Attention weight coefficient, indicating the influence degree of node j on node i;

[0105] : Hidden state of node j in the k-th layer;

[0106] : Vector concatenation operator;

[0107] : Set of neighbor nodes of node i;

[0108] : Aggregated message received by node i in the k-th layer;

[0109] : Learnable aggregation weight matrix;

[0110] State update:

[0111] ;

[0112] : Hidden state of node i in the (k + 1)-th layer;

[0113] : Hidden state of node i in the k-th layer;

[0114] : Aggregated message received by node i in the k-th layer;

[0115] : Gated recurrent unit;

[0116] Step 4, the model outputs the adjustment amount of the current robot speed;

[0117] In an embodiment of the present invention, an MLP is applied to perform the model output, and the specific formula is as follows:

[0118] ;

[0119] ;

[0120] : Adjustment amount of the speed predicted by the i-th robot;

[0121] : Multilayer perceptron;

[0122] : The hidden state of node i in the K-th layer after K-layer propagation;

[0123] : The new adjusted speed of the i-th robot;

[0124] : The speed of the i-th robot;

[0125] In an embodiment of the present invention, there are physical and dynamic constraints on speed and acceleration, and the specific constraint conditions are:

[0126] ;

[0127] ;

[0128] ;

[0129] ;

[0130] : The lower speed limit;

[0131] : The upper speed limit;

[0132] : The new adjusted speed of the i-th robot;

[0133] : The new adjusted speed of the j-th robot;

[0134] : The new adjusted acceleration of the i-th robot;

[0135] : The maximum allowable acceleration;

[0136] : The Euclidean distance between the i-th robot and the j-th robot;

[0137] : The safety distance threshold;

[0138] : The speed of the i-th robot;

[0139] : The time step;

[0140] In an embodiment of the present invention, the aforementioned MLP, GRU, and GNN all need to update their parameters through training. They can be jointly trained with the MLP that executes step 4. In an embodiment of the present invention, they are jointly trained by an unsupervised learning method, and a loss function is designed, such as:

[0141] ;

[0142] ;

[0143] ;

[0144] ;

[0145] : Loss term for safety;

[0146] : Loss term for smoothness;

[0147] : Loss term for efficiency;

[0148] : Safety distance threshold;

[0149] : Euclidean distance between the i-th robot and the j-th robot;

[0150] : New acceleration adjusted for the i-th robot;

[0151] : New speed adjusted for the i-th robot;

[0152] : Desired speed;

[0153] , , : First, second, and third weight coefficients;

[0154] : Total reward function;

[0155] Step 204, determine whether the next section and the end point of the next section are in the exclusive area; if there are other robots in the exclusive area, the scheduling system instructs the robot to wait at the current station; if there are no other robots in the exclusive area, the robot obtains the right of way;

[0156] In one embodiment of the present invention, in the exclusive area, there can be at most one robot.

[0157] Step 300: After the robot obtains the passage permission, it occupies the next section and the end point of the next section. The scheduling system instructs the robot to move towards the end point of the next section. When the robot has traveled a specified distance on the section, the starting point of this section is released. This specified distance is set as the maximum length of the robot plus the safety margin and the positioning error. When the robot reaches the end point of the section, this section is released;

[0158] Step 400: Each robot repeats Steps 100 - 300 until all robots reach the end point of the task.

[0159] In an embodiment of the present invention, the scheduling system has an input parameter planDist, which is the distance that the scheduling system plans in advance for the robot to walk each time, and the default value is 3 meters. The scheduling system calculates whether the sum of the lengths of the occupied sections is less than planDist. If it is less than planDist, then continue to judge whether the robot can reach the next section and the end point of the next section according to the above Steps 201 - 204. The sections occupied by the robot, that is, the sections allocated to the robot by the scheduling system, are the routes that the robot must travel. If it is greater than planDist, then the judgment of the current robot in this round of planning ends, and continue to plan the next robot until the judgment of all robots in this round of planning ends.

[0160] In an embodiment of the present invention, a robot path planning system based on an avoidance strategy is used to execute the above-mentioned robot path planning method based on an avoidance strategy.

[0161] The above describes the embodiments of the present invention, but these embodiments are not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative rather than restrictive. Under the inspiration of this embodiment, those of ordinary skill in the art can also make more equivalent embodiments in various forms, all of which fall within the protection scope of this embodiment.

Claims

1. A robot path planning method based on avoidance strategy, characterized in that: The following steps are involved: Step 100, the scheduling system generates a movement route according to the current station of the robot and the task target station; Step 200, the dispatching system calculates whether the sum of the lengths of the sections currently occupied by the robot is less than planDist based on the generated motion route. If so, it determines whether steps 201-204 are satisfied, and grants the robot corresponding access rights based on whether steps 201-204 are satisfied. Steps 201-204 are as follows: Step 201, perform deadlock detection to determine whether the current robot will be deadlocked with other robots when driving to the end of the next road segment; if not, proceed to step 202; if it occurs and can be resolved, generate a waiting instruction for the current station; if it occurs and cannot be resolved, adopt an avoidance strategy; Step 202, the dispatching system determines whether the next segment and the end point of the next segment are occupied by other robots; if the next segment or the end point of the next segment is occupied by other robots, the dispatching system instructs the robot to wait at the current station; if the robot has occupied the next segment and the end point of the next segment, the dispatching system instructs the robot to move to the end point of the next segment; if the next segment and the end point of the next segment are not occupied, the judgment step 203 is performed; Step 203, the dispatching system uses a collision detection method to determine whether the robot will collide with other robots when traveling to the end of the next road segment according to the length, width and driving direction of the robot; if there is a collision, the dispatching system adopts a speed adjustment strategy for the robot; if there is no collision, the judgment step 204 is performed; Step 204, determine whether the next segment and the end point of the next segment are in the mutually exclusive area; if there are other robots in the mutually exclusive area, the dispatching system instructs the robot to wait at the current station; if there are no other robots in the mutually exclusive area, the robot obtains the right of passage; Step 300, after the robot obtains the right of passage, the robot occupies the next road section and the end point of the next road section. The dispatching system instructs the robot to move to the end point of the next road section. When the robot travels a specified distance on the road section, the starting point of the road section is released. The specified distance is set to the maximum length of the robot plus the safety margin and the positioning error. When the robot travels to the end point of the road section, the road section is released. Step 400, each robot repeats steps 100-300 until all robots reach the end of the task; The speed adjustment strategy is as follows: Step 1, obtain the status information of the current robot and other robots in the scene at the current time step; Step 2: construct a directed graph G(V,E) for the state information of multiple robots obtained at the current time step, where each robot is a node, the edge represents the influence relationship of each robot, and the node feature is the state information feature of the robot; Step 3, constructing a speed adjustment model; Step 4, the model outputs the adjustment amount of the current robot speed; The loss function of the speed adjustment model is: ； ； ； ； : Safety loss item; : Smoothness loss term; : efficiency loss term; : safety distance threshold; : The Euclidean distance between the i-th robot and the j-th robot; : The new acceleration of the i-th robot after adjustment; : The new speed of the i-th robot after adjustment; : expected speed; , , : The first, second and third weight coefficients; : Total reward function.

2. A robot path planning method based on avoidance strategy according to claim 1, characterized in that: The deadlock detection method is as follows: If the two robots are about to deadlock, the judgment method is that the remaining path of robot No. 1 is about to pass through the occupied station of robot No. 2 or the associated station of the occupied station, and the remaining path of robot No. 2 is about to pass through the next station of robot No. 1 or its associated station, then robot No. 1 needs to stop at the current station and wait for robot No. 2 to pass through the next station of robot No. 1 or its associated station; The associated site of a site means that if there is a robot on the site, there cannot be other robots on its associated site at the same time, otherwise a collision will occur. These sites are called the associated sites of the site; the remaining path of the robot refers to the path of the robot from the current site to the end point of the current task, excluding the path the robot has already traveled.

3. A robot path planning method based on avoidance strategy according to claim 1, characterized in that: The avoidance strategy is as follows: If there is a fixed avoidance point in the scene, select a deadlocked robot and look for the nearest avoidance point that is not occupied by other robots and will not cause deadlock with other robots when reaching the avoidance point. If an avoidance point that meets this condition is found, occupy the avoidance point and update the path to this avoidance point; if not found, choose the path with the minimum cost in the event of deadlock to update the path; if there is no fixed avoidance point in the scene, select an idle storage site or an idle stop point as a temporary avoidance point; If the deadlock is still not resolved after executing the above avoidance strategy, add robots that need to execute the avoidance strategy one by one and repeat the above avoidance strategy until the deadlock is resolved.

4. A robot path planning method based on avoidance strategy according to claim 1, characterized in that: The collision detection method is: based on the two rectangular bounding boxes formed by the length, width, driving direction angle, safety margin and positioning error of the two robots, determine whether the two bounding boxes intersect. If they intersect, the two robots will collide, otherwise there will be no collision; the default value of the safety margin is 300mm, and the default value of the positioning error is 20mm.

5. A robot path planning method based on avoidance strategy according to claim 1, characterized in that: The scheduling system has an input parameter planDist, which is the distance that the scheduling system plans the robot to walk in advance each time, and the default value is 3 meters; the scheduling system calculates whether the sum of the lengths of the occupied sections is less than planDist; if it is less than planDist, it continues to determine whether the robot can walk to the next section and the end of the next section according to steps 201-204; the section occupied by the robot, that is, the section allocated to the robot by the scheduling system is the route that the robot must travel; if it is greater than planDist, the current robot in this round of planning is judged to be over, and the next robot is planned until all robots in this round of planning are judged to be over.

6. A robot path planning method based on avoidance strategy according to claim 1, characterized in that: There can be at most one robot in the mutually exclusive zone.

7. A robot path planning system based on avoidance strategy, characterized in that: It is used to execute a robot path planning method based on an avoidance strategy as described in any one of claims 1-6.

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