Mover path optimization method and apparatus, and electronic device and storage medium

Abstract

The embodiments of the present application belong to the field of path planning. Provided are a mover path optimization method and apparatus, and an electronic device and a storage medium. The method comprises: acquiring current three-dimensional map data of a target mover, wherein the current three-dimensional map data comprises map node objects, and the map node objects comprise a starting-point node object, an end-point node object and candidate node objects; adding the candidate node objects to a preset priority queue on the basis of the current three-dimensional map data, the starting-point node object and the end-point node object, so as to obtain a current priority queue, and performing path backtracking to obtain a current optimized path; acquiring three-dimensional map data of the target mover traveling to the next map node object along the current optimized path, so as to obtain next three-dimensional map data; performing node object adjustment on the current priority queue on the basis of the next three-dimensional map data, so as to obtain an updated priority queue; and performing path backtracking on the updated priority queue, so as to obtain an updated optimized path.

Description

Mover path optimization method and device, electronic device and storage medium

[0001] Related applications

[0002] This application claims priority to Chinese patent application number 202410138438X, filed on January 31, 2024, entitled “Mover path optimization method and device, electronic device and storage medium,” the entire text of which is hereby incorporated by reference. Technical Field

[0003] The present application relates to the field of path planning, and in particular to a mover path optimization method and device, electronic equipment, and storage medium. Background Art

[0004] A magnetically driven conveyor line is a conveying system based on magnetic levitation. In this system, workpieces are placed on a mover and transported by the mover. However, the mover must follow a pre-set path during transport. To prevent collisions, the mover must wait until the previous mover has completed its journey before the next mover can begin transporting. This inability to flexibly utilize the transport path results in low transport efficiency. Therefore, improving transport efficiency and flexibility has become a pressing issue.

[0005] Summary of the Invention

[0006] The main purpose of the embodiments of the present application is to propose a mover path optimization method and device, electronic equipment and storage medium, aiming to improve the efficiency and flexibility of mover transportation.

[0007] To achieve the above objectives, a first aspect of an embodiment of the present application provides a mover path optimization method, the method comprising:

[0008] Acquiring three-dimensional map data of the target mover at a current time node to obtain current three-dimensional map data; wherein the current three-dimensional map data is constructed by the map data at the current time node and the movement data of the mover traveling on the map, and includes map node objects, and the map node objects include a starting node object, an end node object, and a plurality of candidate node objects of the target mover;

[0009] Adding the candidate node object to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object to obtain a current priority queue;

[0010] Perform path backtracking on the current priority queue to obtain a current optimized path;

[0011] Acquiring the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object to obtain next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data of the next time node and the movement data of the mover traveling on the map;

[0012] Adjusting the node objects of the current priority queue according to the next three-dimensional map data to obtain an updated optimized path;

[0013] Perform path backtracking on the update priority queue to obtain an updated optimized path.

[0014] In some embodiments, the current three-dimensional map data includes: motion data of the target mover and motion data of non-target movers; and adding the candidate node object to a preset priority queue based on the current three-dimensional map data, the starting node object, and the ending node object to obtain a current priority queue includes:

[0015] Filtering the map node objects according to the candidate node objects adjacent to the starting point node object to obtain a selected node object;

[0016] Constructing the road segment loss data between the starting node object and the selected node object according to the starting node object, the selected node object, the motion data of the target mover and the motion data of the non-target mover;

[0017] The selected node object is added to a preset priority queue according to the road section loss data and the terminal node object to obtain a current priority queue.

[0018] In some embodiments, before backtracing the path of the current priority queue to obtain the current optimized path, the method further includes:

[0019] Searching the map node object in the current priority queue to obtain a queue search result; wherein the queue search result is characterized by whether the map node object exists in the priority queue;

[0020] If the queue search result indicates that the map node object does not exist in the priority queue, a path search failure message is output.

[0021] In some embodiments, constructing the segment loss data between the starting node object and the selected node object based on the motion data of the starting node object, the selected node object, the target mover, and the motion data of the non-target mover includes:

[0022] Acquire the travel section of the selected node object and the starting point node object to obtain the selected section;

[0023] screening the motion data of the non-target movers according to the non-target movers traveling on the selected road section to obtain the motion data of the selected non-target movers;

[0024] Obtaining the travel section length of the selected section to obtain a selected length;

[0025] Obtaining the curvature of the selected road section to obtain a selected curvature;

[0026] Obtaining a planned workstation distance, a maximum planned speed, and a planned mover speed between the selected node object and the starting node object;

[0027] The road section loss data is constructed according to the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed.

[0028] In some embodiments, the loss weight data includes: collision time loss weight, collision distance loss weight, longitudinal acceleration change rate loss weight, acceleration loss weight, curvature weight, position difference loss weight and speed loss weight; the selected non-target mover motion data includes: selected non-target mover motion speed; the target mover motion data includes: target mover motion speed, longitudinal acceleration change rate, acceleration; the section loss data is constructed based on the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed, including:

[0029] constructing a collision distance according to the selected length, the non-target mover movement speed, and the target mover movement speed;

[0030] Constructing a collision time according to the collision distance, the motion speed of the non-target mover, and the motion speed of the target mover;

[0031] Constructing safety loss data according to the collision time, the collision distance, the collision time loss weight, and the collision distance loss weight;

[0032] constructing stability loss data according to the longitudinal acceleration change rate, the longitudinal acceleration change rate loss weight, the acceleration, the acceleration loss weight, the target mover motion speed, the selected curvature, and the curvature weight;

[0033] Constructing efficiency loss data according to the position difference loss weight, the workstation planning distance, the maximum planning speed, and the mover planning speed;

[0034] The road section loss data is constructed according to the safety loss data, the stability loss data, and the efficiency loss data.

[0035] In some embodiments, adding the selected node object to a preset priority queue based on the road segment loss data and the terminal node object to obtain a current priority queue includes:

[0036] Arrange the selected node objects in ascending order according to the road section loss data of the selected node objects to obtain an ascending sequence of node objects;

[0037] The selected node object is added to the priority queue according to the ascending sequence of the node objects and the end node object to obtain the current priority queue.

[0038] In some embodiments, before obtaining the three-dimensional map data of the target mover at the current time node, the process further includes:

[0039] Acquiring line position information and obstacle marking information of each conveyor line at different time nodes; wherein the obstacle marking information represents obstacles on the conveyor line that affect the travel of the target mover;

[0040] A map is constructed according to the route position information and the obstacle marking information to obtain the three-dimensional map data at different time nodes.

[0041] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a mover path optimization device, the device comprising:

[0042] A first acquisition module is configured to acquire three-dimensional map data of a target mover at a current time node to obtain current three-dimensional map data; wherein the current three-dimensional map data is constructed by the map data at the current time node and motion data of the mover traveling on the map, and includes map node objects, wherein the map node objects include a start node object, an end node object, and a plurality of candidate node objects of the target mover;

[0043] an adding module, configured to add the candidate node object to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object, to obtain a current priority queue;

[0044] A first backtracking module, configured to perform path backtracking on the current priority queue to obtain a current optimized path;

[0045] a second acquisition module, configured to acquire the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object, thereby obtaining next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data of the next time node and the movement data of the mover traveling on the map;

[0046] an adjustment module, configured to adjust node objects of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue;

[0047] The second backtracking module is used to backtrack the path of the update priority queue to obtain an updated optimized path.

[0048] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0049] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method described in the first aspect.

[0050] The present application proposes a mover path optimization method and device, electronic device and storage medium, which obtains three-dimensional map data of the current time node of the target mover, wherein the current three-dimensional map data includes map node objects, and the map node objects include the starting node object, the end node object and multiple candidate node objects of the target mover; then, according to the current three-dimensional map data, the starting node object and the end node object, the candidate node objects are added to a preset priority queue to obtain the current priority queue; then, the path is backtraced according to the current priority queue to obtain the current optimized path, which can make real-time road condition judgments based on the map data of the target mover at the current moment, select the candidate node objects between the starting node object and the end node object, and use the priority queue to obtain the optimized path, thereby improving the flexibility and efficiency of the target mover during the operation of the conveyor line. By obtaining the next three-dimensional map data corresponding to the time node after the target mover travels to the next map node object along the optimized path; adjusting the nodes of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue; and then backtracing the path according to the updated priority queue to obtain an updated optimized path, it is possible to make judgments based on the real-time road conditions at different times and the motion data of multiple movers in the map, select a path that is more favorable for the transportation process of the target mover, and adjust the path in real time, thereby reducing the loss of the target mover on the conveyor line and improving the efficiency and flexibility of the transportation of the target mover on the conveyor line. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the conventional technology, the following briefly introduces the drawings required for use in the embodiments or the conventional technology descriptions. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the disclosed drawings without any creative work.

[0052] FIG1 is a flow chart of a mover path optimization method provided in an embodiment of the present application.

[0053] FIG2 is a flow chart of another mover path optimization method provided in an embodiment of the present application.

[0054] FIG3 is a flowchart of step S102 in FIG1 .

[0055] FIG. 4 is a flowchart of step S302 in FIG. 3 .

[0056] FIG. 5 is a flowchart of step S406 in FIG. 4 .

[0057] FIG6 is a flowchart of step S303 in FIG3 .

[0058] FIG7 is a flow chart of another mover path optimization method provided in an embodiment of the present application.

[0059] FIG8 is a schematic structural diagram of a mover path optimization device provided in an embodiment of the present application.

[0060] FIG9 is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application.

[0061] Figure 10 is a driving route map of the mover road strength optimization method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0063] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0064] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0065] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0066] First, let’s analyze some of the terms used in this application:

[0067] Priority Queue: A data structure in which each element is associated with a priority or weight, and the order in which elements are processed is based on their priority rather than the order in which they were inserted. It belongs to the field of data structures and algorithms in computer science. It can be used to quickly access and process the elements with the highest priority in a data set, and is often used in scenarios such as task scheduling, graph algorithms, and simulation systems. In operating systems, priority queues can be used to manage the priority of process scheduling to ensure that high-priority tasks are executed first.

[0068] Curvature: A physical quantity that describes the degree of curvature of a curve at a certain point. It belongs to the disciplines of mathematics and physics. It can be used to describe the curvature of a curve or surface in space and is widely used in fields such as geometry, calculus, and astronomy. In engineering design, curvature is also often used to optimize the design of curves to meet specific requirements, such as ensuring smooth turns in road design.

[0069] A magnetically driven conveyor line is a conveying system based on magnetic levitation. In this system, workpieces are placed on a mover and transported by the mover. However, the mover must follow a pre-set path during transport. To prevent collisions, the mover must wait until the previous mover has completed its journey before the next mover can begin transporting. This inability to flexibly utilize the transport path results in low transport efficiency. Therefore, improving transport efficiency and flexibility has become a pressing issue.

[0070] Based on this, the embodiments of the present application provide a mover path optimization method and device, electronic equipment and storage medium, aiming to improve the efficiency and flexibility of mover transportation.

[0071] The embodiments of the present application provide a mover path optimization method and device, electronic device, and storage medium, which are specifically illustrated through the following embodiments. First, the mover path optimization method in the embodiments of the present application is described.

[0072] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0073] The method for optimizing the path of an actuator provided in the embodiment of the present application relates to the field of path planning. The method for optimizing the path of an actuator provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN, content distribution network), and big data and artificial intelligence platforms; the software can be an application that implements the method for optimizing the path of an actuator, etc., but is not limited to the above forms.

[0074] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0075] FIG1 is an optional flow chart of a mover path optimization method provided in an embodiment of the present application. The method in FIG1 may include but is not limited to steps S101 to S106 .

[0076] Step S101: Acquire three-dimensional map data of a target mover at a current time node to obtain current three-dimensional map data; wherein the current three-dimensional map data is constructed by the map data at the current time node and the movement data of the mover traveling on the map, and includes map node objects, which include a start node object, an end node object, and multiple candidate node objects of the target mover;

[0077] Step S102, adding candidate node objects to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object to obtain a current priority queue;

[0078] Step S103, backtracking the path of the current priority queue to obtain the current optimized path;

[0079] Step S104: Acquire the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object, thereby obtaining the next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data of the next time node and the movement data of the mover traveling on the map;

[0080] Step S105, adjusting the node objects of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue;

[0081] Step S106: backtrack the path of the updated priority queue to obtain an updated optimized path.

[0082] Steps S101 to S106 shown in the embodiment of the present application are performed by obtaining the three-dimensional map data of the current time node of the target mover, wherein the current three-dimensional map data includes a map node object, and the map node object includes a starting node object, an end node object and multiple candidate node objects of the target mover; then, the candidate node object is added to a preset priority queue according to the current three-dimensional map data, the starting node object and the end node object to obtain the current priority queue; then, the path is backtraced according to the current priority queue to obtain the current optimized path, which can make real-time road condition judgments based on the map data of the target mover at the current moment, select the candidate node objects between the starting node object and the end node object, and use the priority queue to obtain the optimized path, thereby improving the flexibility and efficiency of the target mover during the operation of the conveyor line. By obtaining the next three-dimensional map data corresponding to the time node after the target mover travels to the next map node object along the optimized path; adjusting the nodes of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue; and then backtracing the path according to the updated priority queue to obtain an updated optimized path, it is possible to make judgments based on the real-time road conditions at different times and the motion data of multiple movers in the map, select a path that is more favorable for the transportation process of the target mover, and adjust the path in real time, thereby reducing the loss of the target mover on the conveyor line and improving the efficiency and flexibility of the transportation of the target mover on the conveyor line.

[0083] Please refer to FIG. 2 . In some embodiments, before step S101 , the mover path optimization method may include but is not limited to steps S201 to S202 :

[0084] Step S201, obtaining line position information and obstacle marking information of each conveyor line at different time nodes; wherein the obstacle marking information represents obstacles on the conveyor line that affect the travel of the target mover;

[0085] Step S201 : constructing a map based on the route location information and obstacle marking information to obtain three-dimensional map data at different time nodes.

[0086] In step S201 of some embodiments, the conveyor line includes many processing stations, and the line position information is the coordinate position information of these processing stations, which is represented by two-dimensional coordinates. Specifically, the line position information is represented by two-dimensional coordinate values ​​(x, y), where x is the horizontal coordinate information of the processing station and y is the vertical coordinate information of the processing station. The obstacle marking information indicates whether the processing station can pass through. When the processing station indicates that it can pass through, the target mover can pass through the processing station. When the processing station indicates that it cannot pass through, the target mover cannot pass through the processing station, that is, the target mover will be blocked and stopped when it travels to the processing station. Specifically, the obstacle flag information is represented by a Boolean value. When the obstacle flag information is "True", the processing station is an obstacle and the target mover cannot pass through. When the obstacle flag information is "False", it indicates that the obstacle is not an obstacle and the target mover can pass through the processing station.

[0087] In step S202 of some embodiments, the three-dimensional map data at different time points includes map data and mover motion data at different time points. The three dimensions of the three-dimensional map data are time, abscissa, and ordinate. The three-dimensional map data includes node information, road segment information, and mover motion data. If a directed path exists between adjacent nodes, i.e., a road segment exists between adjacent nodes for the target mover to travel, then road segment information exists between the two nodes. If a mover travels on a directed path, the road segment information also includes the mover's motion data.

[0088] In one embodiment, the node information includes: node coordinate information, obstacle information, and parent node information, wherein the parent node information indicates the previous node of the node in the path, which is used when tracing the path back and can guide the optimal path from the starting point to the end point. By recording the parent node of each node, after finding the end point, reverse traversal is performed according to the parent node to obtain the complete path. The road section information includes: the maximum speed that the section can travel, indicating the maximum speed that the mover can reach on the section, acceleration, indicating the acceleration limit of the mover on the section, the number of cars, indicating the number of cars currently existing on the section, safety distance, indicating the minimum adjacent distance between two adjacent movers, length, indicating the physical distance of the section, type, indicating the type of the section, which can be a straight line, an arc, or a combination of a straight line and an arc. The type information of the section helps to more accurately describe the shape and properties of the section. Because the speed loss of the mover when traveling on an arc is greater than the speed loss when traveling on a straight line, the priority of a straight line section is higher than that of an arc section. The mover motion data includes: target mover jerk, target mover acceleration, target mover velocity, target mover position, target mover acceleration time, front mover jerk, front mover acceleration, front mover velocity, front mover position, and front mover acceleration time.

[0089] Steps S201 to S202 shown in the embodiment of the present application construct a map by acquiring the line position information and obstacle marking information on the conveyor line at different time nodes, and obtain three-dimensional map data at different time nodes, thereby providing a data basis for subsequent target movers based on the road condition information at different time nodes, so that the target movers can optimize the path according to the real-time road conditions.

[0090] In step S101 of some embodiments, the map node objects are different workstations on the conveyor line, and the map node objects include location information, road section information, and mover motion information; the map node objects can be divided into starting node objects, end node objects, and candidate node objects. The starting node object is the starting point when the target mover performs path planning, the end node object is the end point when the target mover performs path planning, and the candidate node objects are nodes that may be traveled between the starting node object and the end node object.

[0091] Referring to FIG. 3 , in step S102 of some embodiments, the mover path optimization method may include but is not limited to steps S301 to S303:

[0092] Step S301, filtering the map node objects according to the candidate node objects adjacent to the starting point node object to obtain a selected node object;

[0093] Step S302, constructing the road segment loss data between the starting node object and the selected node object based on the motion data of the starting node object, the selected node object, the target mover, and the motion data of the non-target mover;

[0094] Step S303: Add the selected node object to a preset priority queue according to the road section loss data and the terminal node object to obtain a current priority queue.

[0095] In step S301 of some embodiments, the selected node object is a map node object adjacent to the starting node object, and adjacent candidate node objects are screened out from the map node objects and map node objects with a one-way path from the starting node object and the adjacent candidate node objects are used as the selected node objects.

[0096] Referring to FIG. 4 , in step S302 of some embodiments, the mover path optimization method may include but is not limited to steps S401 to S406:

[0097] Step S401, obtaining the travel section of the selected node object and the starting node object to obtain the selected section;

[0098] Step S402, screening the motion data of the non-target movers according to the non-target movers traveling on the selected road section to obtain the motion data of the selected non-target movers;

[0099] Step S403, obtaining the travel section length of the selected section to obtain the selected length;

[0100] Step S404, obtaining the road section curvature of the selected road section to obtain a selected curvature;

[0101] Step S405, obtaining the planned workstation distance, maximum planned speed, and mover planned speed between the selected node object and the starting node object;

[0102] Step S406 , constructing the section loss data according to the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed.

[0103] In step S401 of some embodiments, a one-way path between the starting node object and the selected node object is used as the selected road segment.

[0104] In step S402 of some embodiments, when the target mover is performing path optimization, there may be other movers traveling on the selected road section, and motion data of the other movers are acquired to obtain motion data of the selected non-target mover.

[0105] In step S404 of some embodiments, the curvature is the road curvature. When a circular arc path exists on the selected road segment, the curvature of the arc is calculated as the selected curvature. When no circular arc path exists, the curvature is zero.

[0106] Referring to FIG. 5 , in step S406 of some embodiments, the mover path optimization method may include but is not limited to steps S501 to S506:

[0107] Step S501, constructing a collision distance according to the selected length, the non-target mover movement speed and the target mover movement speed;

[0108] Step S502, constructing a collision time according to the collision distance, the non-target mover movement speed, and the target mover movement speed;

[0109] Step S503, constructing safety loss data based on the collision time, collision distance, collision time loss weight, and collision distance loss weight;

[0110] Step S504, constructing stable loss data according to the longitudinal acceleration change rate, the longitudinal acceleration change rate loss weight, the acceleration, the acceleration loss weight, the target mover motion speed, the selected curvature and the curvature weight;

[0111] Step S505 , constructing efficiency loss data based on the position difference loss weight, the workstation planning distance, the maximum planning speed, and the mover planning speed;

[0112] Step S506: Constructing the road section loss data according to the safety loss data, stability loss data, and efficiency loss data.

[0113] In step S501 of some embodiments, the collision distance is the distance that the target mover decelerates to avoid colliding with the previous mover on the selected road segment when there are other movers moving on the selected road segment and the target mover travels to the selected node object at the target mover's speed. When the target mover travels along the road segment from one map node object to the next map node object, where it would collide with the previous mover on the road segment, the target mover decelerates until it maintains a safe distance from the previous mover and its speed remains the same as the previous mover's speed. This decelerated distance is the collision distance.

[0114] In step S502 of some embodiments, the collision time is the time during which the target moving object decelerates to avoid colliding with the previous moving object on the road segment. When the target moving object travels from one map node object along the road segment to the next map node object, where a collision with the previous moving object is imminent, the target moving object decelerates until it maintains a safe distance from the previous moving object and its speed remains the same. This period of deceleration is the collision time.

[0115] In step S503 of some embodiments, the safety loss is the loss data considered when there is an obstacle in front of the target mover, which is used to balance the safety loss of the mover and to avoid the situation where the following distance is too close. In some embodiments, the calculation expression of the safety loss data is shown in formula (1):

[0116] Among them, C1 is the safety loss data, t col is the collision time, t0 is the starting time of the target mover’s uniform motion before braking, S col is the collision distance, S0 is the starting position of the target mover, w tcc is the collision time loss weight, w d Collision path loss weight.

[0117] In step S504 of some embodiments, the stability loss data is the data considered for the target motor to travel smoothly during the selected road section. It is used to ensure the stable travel of the target motor. It is necessary to consider the longitudinal acceleration change rate of the target motor, the acceleration, and the road curvature. When the curvature is large, the target motor is expected to have a smaller speed. In some embodiments, the calculation expression of the stability loss data is shown in formula (2): C2 = w j jerk 2 +w a a+w k kv2 , (2)

[0118] Among them, C2 represents the stable loss data, w j Indicates the longitudinal acceleration rate loss weight, jerk 2 represents the rate of change of longitudinal acceleration, w a represents the acceleration loss weight, a represents acceleration, w k represents the curvature loss weight, k represents the selected curvature, v 2 Indicates the target mover movement speed.

[0119] In step S505 of some embodiments, the efficiency loss data is the data considered in order to ensure that the speed of the target mover does not exceed the speed set for the selected road during the driving process of the target mover on the selected road section. The workstation planning distance is the physical distance between the workstation of the target mover from the starting node object to the workstation of the selected node, the maximum planning speed is the maximum speed acceptable on the selected road section, and the mover planning speed is the maximum speed that the target mover can reach after loading the workpiece. Different workpieces have different mover planning speeds. In some embodiments, the calculation expression of the efficiency loss data is shown in formula (3): C3=w s (S max -S0)+w v (v max -v0), (3)

[0120] Among them, C3 represents the efficiency loss data, w s Represents the position difference loss weight, S max Indicates the end point of the workstation planning distance, S0 indicates the current position of the target mover, v max represents the maximum planning speed, v0 represents the moving part planning speed, w v Represents the speed difference loss weight.

[0121] In step S506 of some embodiments, the calculation method of the road segment loss data is as shown in formula (4): P = AC1 + BC2 + DC3, (4)

[0122] Where P is the road section loss data, C1 represents the safety loss data, C2 represents the stability loss data, C3 represents the efficiency loss data, and A, B and C are constants.

[0123] Steps S501 to S506 shown in the embodiment of the present application calculate the section loss data comprehensively based on the section information, the mover motion information, and the map node object, so that the target mover can make judgments based on the section loss data when selecting the path optimization and select the optimal candidate node object.

[0124] Steps S401 to S406 shown in the embodiment of the present application construct section loss data by acquiring target mover motion data, non-target mover motion data, selected length of the selected section, selected curvature, workstation planning distance, maximum planning speed and mover planning speed, and comprehensively consider real-time road conditions so that the target mover can judge the current real-time road conditions, select the optimal candidate node object, and improve the efficiency and flexibility of the target mover.

[0125] Referring to FIG. 6 , in step S303 of some embodiments, the mover path optimization method may include but is not limited to steps S601 to S602:

[0126] Step S601, arranging the selected node objects in ascending order according to the road section loss data of the selected node objects to obtain an ascending sequence of the node objects;

[0127] Step S602 : adding the selected node object to the priority queue according to the ascending sequence of the node objects and the end node object to obtain the current priority queue.

[0128] In step S602 of some embodiments, the selected node objects are added to the priority queue in the order of the node object ascending sequence. At this time, the nodes of the priority queue are placed in the order of the road loss data from small to large.

[0129] Steps S601 to S602 shown in the embodiment of the present application, by sorting the selected node objects in ascending order and placing them into the priority queue to obtain the current priority queue, can enable the target mover to select the next map node object according to the road section loss data when obtaining the next map node object, give priority to the map node object with small road section loss data, reduce the consumption required for the target mover to travel, and improve the efficiency of the target mover.

[0130] In step S103 of some embodiments, the current priority queue includes map node objects and end node objects obtained by continuously selecting candidate map node objects based on road loss data starting from the starting point. The parent node information in the map node object and the end node object records the previous map node object where the target mover is located. The path backtracking is to perform reverse traversal based on the parent node information of the parent node of the end point to obtain the previous map node object where the target mover is located, that is, the first reverse map node object, and then obtain the second reverse map node object based on the parent node information of the first reverse map object. The cycle is repeated in sequence to obtain the reverse path from the end point to the starting point. Finally, the reverse path is reversely processed to obtain the forward path, that is, the current optimization queue.

[0131] In one embodiment, the current priority path has the following nodes: a starting node object whose parent node information is empty, a first map node object whose parent node information is the starting node object, a second map node object whose parent node information is the first map node object, and an end node object whose parent node information is the second map node object. Path backtracking is performed based on the objects in the priority queue. First, the parent node information of the end node object is obtained to obtain the second map node object. Then, based on the parent node information of the second map node object, the first map node object is obtained. Then, based on the parent node information of the first map node object, the starting node object is obtained. That is, a reverse path exists, which is the end node object, the second map node object, the first map node object, and the starting node object. The reverse path is reversed to obtain a forward path, which is the starting node object, the first map node object, the second map node object, and the end node object.

[0132] Please refer to FIG. 7 . In some embodiments, after step S103 , the mover path optimization method may include but is not limited to steps S701 to S702 :

[0133] Step S701: Search for a map node object in the current priority queue to obtain a queue search result; wherein the queue search result indicates whether the map node object exists in the priority queue;

[0134] Step S702: If the queue search result indicates that the priority queue does not contain the map node object, a path search failure message is output.

[0135] In step S701 of some embodiments, a search is performed for nodes in the current priority queue to determine whether a map node object exists. If a map node object exists in the current optimized path, it indicates that the target mover can travel from the starting node object to the end node object under the current three-dimensional map data.

[0136] In step S702 of some embodiments, when the queue search result indicates that there is no map node object in the priority queue, path search failure information is output. In some embodiments, the path search failure information includes target mover information, starting point node object, end point node object and current three-dimensional map data.

[0137] In steps S701 to S702 shown in the embodiment of the present application, whether the target moving element can travel from the starting point to the end node object is determined by searching the map node objects in the current priority queue to see whether there is an end node object.

[0138] In step S104 of some embodiments, after the target moving element moves along the current optimized path to the next map node object, the next three-dimensional map data is acquired according to the time when the target moving element is at the next map node object.

[0139] Referring to FIG. 10 , in one embodiment, the target vehicle starts from the starting point (1, 1), calculates the road loss data between the starting point and node (1, 2) as 1, and the road loss data between the starting point and node (2, 1), sorts nodes (1, 2) and (2, 1) in ascending order of the road loss data and places them into a priority queue, and then drives to node (1, 2) according to the nodes in the priority queue, as shown in the first state in the figure. Further, after the target vehicle arrives at node (1, 2), the first three-dimensional map data is obtained based on the time when the target vehicle arrives at node (1, 2), and the vehicle drives to node (2, 2) according to the first three-dimensional map data, as shown in the second state in the figure. Further, the second three-dimensional map data is obtained based on the time when the target vehicle arrives at node (1, 2), and the vehicle drives to node (2, 1) according to the second three-dimensional map data. Further, the target vehicle drives to node (3, 1) and node (3, 2) in sequence, as shown in the third state in the figure. Furthermore, the third three-dimensional map data is obtained when the target moving part travels to the node (3,2). At this time, the target moving part can travel to the terminal node object, and the target moving part directly travels to the terminal node object (3,3).

[0140] Referring to FIG8 , an embodiment of the present application further provides a mover path optimization device that can implement the above-mentioned mover path optimization method. The device includes:

[0141] A first acquisition module 801 is configured to acquire three-dimensional map data of a target mover at a current time node, thereby obtaining current three-dimensional map data. The current three-dimensional map data is constructed from the map data at the current time node and the movement data of the mover traveling on the map, and includes map node objects. The map node objects include a start node object, an end node object, and multiple candidate node objects of the target mover.

[0142] An adding module 802 is configured to add candidate node objects to a preset priority queue according to current three-dimensional map data, a starting node object, and an ending node object, to obtain a current priority queue;

[0143] The first backtracking module 803 is used to backtrack the path of the current priority queue to obtain the current optimized path;

[0144] The second acquisition module 804 is configured to acquire the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object, thereby obtaining the next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data at the next time node and the movement data of the mover traveling on the map;

[0145] An adjustment module 805 is configured to adjust the node objects of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue;

[0146] The second backtracking module 806 is configured to backtrack the path of the updated priority queue to obtain an updated optimized path.

[0147] In one embodiment, the current three-dimensional map data includes: motion data of the target mover and motion data of non-target movers; the adding module includes:

[0148] A screening module, configured to screen the map node objects according to the candidate node objects adjacent to the starting node object to obtain a selected node object;

[0149] A first construction module is configured to construct the road segment loss data between the starting node object and the selected node object according to the starting node object, the selected node object, the motion data of the target mover, and the motion data of the non-target mover;

[0150] An adding submodule is used to add the selected node object to a preset priority queue according to the road section loss data and the terminal node object to obtain a current priority queue.

[0151] In one embodiment, the first building block includes:

[0152] A first acquisition submodule is used to acquire the travel section of the selected node object and the starting node object to obtain the selected section;

[0153] a screening submodule, configured to screen the motion data of the non-target movers according to the non-target movers traveling on the selected road section to obtain the motion data of the selected non-target movers;

[0154] A second acquisition submodule is used to acquire the travel section length of the selected section to obtain a selected length;

[0155] A third acquisition submodule is used to acquire the road section curvature of the selected road section to obtain a selected curvature;

[0156] A fourth acquisition submodule is used to obtain a planned workstation distance, a maximum planned speed, and a planned mover speed between the selected node object and the starting node object;

[0157] A construction submodule is used to construct the road section loss data based on the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed.

[0158] In one embodiment, the loss weight data includes: collision time loss weight, collision distance loss weight, longitudinal acceleration change rate loss weight, acceleration loss weight, curvature weight, position difference loss weight and speed loss weight; the selected non-target mover motion data includes: selected non-target mover motion speed; the target mover motion data includes: target mover motion speed, longitudinal acceleration change rate, acceleration; the construction submodule includes:

[0159] a first constructing unit, configured to construct a collision distance according to the selected length, the motion speed of the non-target mover, and the motion speed of the target mover;

[0160] a second constructing unit, configured to construct a collision time according to the collision distance, the motion speed of the non-target mover, and the motion speed of the target mover;

[0161] a third constructing unit, configured to construct safety loss data according to the collision time, the collision distance, the collision time loss weight, and the collision distance loss weight;

[0162] a fourth constructing unit, configured to construct stability loss data according to the longitudinal acceleration change rate, the longitudinal acceleration change rate loss weight, the acceleration, the acceleration loss weight, the target mover motion speed, the selected curvature, and the curvature weight;

[0163] a fifth constructing unit, configured to construct efficiency loss data according to the position difference loss weight, the workstation planning distance, the maximum planning speed, and the mover planning speed;

[0164] The sixth construction unit is used to construct the road section loss data according to the safety loss data, the stability loss data, and the efficiency loss data.

[0165] In one embodiment, the adding submodule includes:

[0166] An arranging unit, configured to arrange the selected node objects in ascending order according to the road section loss data of the selected node objects to obtain an ascending sequence of node objects;

[0167] An adding unit is used to add the selected node object to the priority queue according to the ascending sequence of the node objects and the end node object to obtain the current priority queue.

[0168] In one embodiment, the apparatus further comprises:

[0169] A search module, configured to search the map node object in the current priority queue to obtain a queue search result; wherein the queue search result indicates whether the map node object exists in the priority queue;

[0170] The output module is configured to output path search failure information if the queue search result indicates that the map node object does not exist in the priority queue.

[0171] In one embodiment, the apparatus further comprises:

[0172] A third acquisition module is configured to acquire line position information and obstacle marking information of each conveyor line at different time nodes; wherein the obstacle marking information represents obstacles on the conveyor line that affect the travel of the target mover;

[0173] The second construction module is used to construct a map according to the route position information and the obstacle mark information to obtain the three-dimensional map data at different time nodes.

[0174] The specific implementation of the mover path optimization device is basically the same as the specific embodiment of the above-mentioned mover path optimization method, and will not be repeated here.

[0175] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described mover path optimization method. The electronic device can be any smart terminal, such as a tablet computer or an in-vehicle computer.

[0176] Please refer to FIG9 , which illustrates a hardware structure of an electronic device according to another embodiment. The electronic device includes:

[0177] The processor 901 may be implemented using a general-purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0178] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute the mover path optimization method of the embodiments of this application;

[0179] Input / output interface 903, used to implement information input and output;

[0180] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as Universal Serial Bus (USB), network cable, etc.) or wireless means (such as mobile network, Wireless Fidelity (WIFI), Bluetooth, etc.);

[0181] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );

[0182] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0183] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned mover path optimization method is implemented.

[0184] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0185] The embodiments of the present application provide a mover path optimization method, a mover path optimization device, an electronic device, and a storage medium. The method obtains three-dimensional map data of the target mover at the current time node, wherein the current three-dimensional map data includes a map node object, and the map node object includes a starting node object, an end node object, and multiple candidate node objects of the target mover; then, according to the current three-dimensional map data, the starting node object, and the end node object, the candidate node object is added to a preset priority queue to obtain a current priority queue; then, the path is backtraced according to the current priority queue to obtain the current optimized path. The method can perform real-time road condition judgment based on the map data of the target mover at the current moment, select the candidate node objects between the starting node object and the end node object, and use the priority queue to obtain the optimized path, thereby improving the flexibility and efficiency of the target mover during the operation of the conveyor line. By obtaining the next three-dimensional map data corresponding to the time node after the target mover travels to the next map node object along the optimized path; adjusting the nodes of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue; and then backtracing the path according to the updated priority queue to obtain an updated optimized path, it is possible to make judgments based on the real-time road conditions at different times and the motion data of multiple movers in the map, select a path that is more favorable for the transportation process of the target mover, and adjust the path in real time, thereby reducing the loss of the target mover on the conveyor line and improving the efficiency and flexibility of the transportation of the target mover on the conveyor line.

[0186] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0187] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0188] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0189] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0190] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0191] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0192] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0193] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0194] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0195] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0196] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

[0197] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0198] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for optimizing a mover path, characterized in that: The method comprises: Acquiring three-dimensional map data of the target mover at a current time node to obtain current three-dimensional map data; wherein the current three-dimensional map data is constructed by the map data at the current time node and the movement data of the mover traveling on the map, and includes map node objects, and the map node objects include a starting node object, an end node object, and a plurality of candidate node objects of the target mover; Adding the candidate node object to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object to obtain a current priority queue; Perform path backtracking on the current priority queue to obtain a current optimized path; Acquiring the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object to obtain next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data of the next time node and the movement data of the mover traveling on the map; Adjusting the node objects of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue; Perform path backtracking on the update priority queue to obtain an updated optimized path.

2. The method according to claim 1, characterized in that The current three-dimensional map data includes: motion data of the target mover and motion data of non-target movers; adding the candidate node object to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object to obtain a current priority queue includes: Filtering the map node objects according to the candidate node objects adjacent to the starting point node object to obtain a selected node object; Constructing the road segment loss data between the starting node object and the selected node object according to the starting node object, the selected node object, the motion data of the target mover and the motion data of the non-target mover; The selected node object is added to a preset priority queue according to the road section loss data and the terminal node object to obtain a current priority queue.

3. The method according to claim 2, characterized in that The step of constructing the section loss data between the starting node object and the selected node object according to the starting node object, the selected node object, the motion data of the target mover, and the motion data of the non-target mover includes: Acquire the travel section of the selected node object and the starting point node object to obtain the selected section; screening the motion data of the non-target movers according to the non-target movers traveling on the selected road section to obtain the motion data of the selected non-target movers; Obtaining the travel section length of the selected section to obtain a selected length; Obtaining the curvature of the selected road section to obtain a selected curvature; Obtaining a planned workstation distance, a maximum planned speed, and a planned mover speed between the selected node object and the starting node object; The road section loss data is constructed according to the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed.

4. The method according to claim 3, characterized in that The loss weight data includes: collision time loss weight, collision distance loss weight, longitudinal acceleration change rate loss weight, acceleration loss weight, curvature weight, position difference loss weight and speed loss weight; the selected non-target mover motion data includes: selected non-target mover motion speed; the target mover motion data includes: target mover motion speed, longitudinal acceleration change rate, acceleration; the section loss data is constructed based on the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed, including: constructing a collision distance according to the selected length, the non-target mover movement speed, and the target mover movement speed; Constructing a collision time according to the collision distance, the motion speed of the non-target mover, and the motion speed of the target mover; Constructing safety loss data according to the collision time, the collision distance, the collision time loss weight, and the collision distance loss weight; constructing stability loss data according to the longitudinal acceleration change rate, the longitudinal acceleration change rate loss weight, the acceleration, the acceleration loss weight, the target mover motion speed, the selected curvature, and the curvature weight; Constructing efficiency loss data according to the position difference loss weight, the workstation planning distance, the maximum planning speed, and the mover planning speed; The road section loss data is constructed according to the safety loss data, the stability loss data, and the efficiency loss data.

5. The method according to claim 2, characterized in that The step of adding the selected node object to a preset priority queue according to the road segment loss data and the terminal node object to obtain a current priority queue includes: Arrange the selected node objects in ascending order according to the road segment loss data of the selected node objects to obtain an ascending sequence of node objects; The selected node object is added to the priority queue according to the ascending sequence of the node objects and the end node object to obtain the current priority queue.

6. The method according to claim 1, characterized in that Before backtracing the path of the current priority queue to obtain the current optimized path, the method further includes: Searching the map node object in the current priority queue to obtain a queue search result; wherein the queue search result is characterized by whether the map node object exists in the priority queue; If the queue search result indicates that the map node object does not exist in the priority queue, a path search failure message is output.

7. The method according to claim 1, characterized in that Before obtaining the three-dimensional map data of the target mover at the current time node and obtaining the current three-dimensional map data, the method further includes: Acquiring line position information and obstacle marking information of each conveyor line at different time nodes; wherein the obstacle marking information represents obstacles on the conveyor line that affect the travel of the target mover; A map is constructed according to the route position information and the obstacle marking information to obtain the three-dimensional map data at different time nodes.

8. A mover path optimization device, characterized in that: The device comprises: A first acquisition module is configured to acquire three-dimensional map data of a target mover at a current time node to obtain current three-dimensional map data; wherein the current three-dimensional map data is constructed by the map data at the current time node and motion data of the mover traveling on the map, and includes map node objects, wherein the map node objects include a start node object, an end node object, and a plurality of candidate node objects of the target mover; an adding module, configured to add the candidate node object to a preset priority queue according to the current three-dimensional map data, the starting node object, and the ending node object, to obtain a current priority queue; A first backtracking module, configured to perform path backtracking on the current priority queue to obtain a current optimized path; a second acquisition module, configured to acquire the three-dimensional map data of the target mover traveling along the current optimized path to the next map node object, thereby obtaining next three-dimensional map data; wherein the next three-dimensional map data is constructed by the map data of the next time node and the movement data of the mover traveling on the map; an adjustment module, configured to adjust node objects of the current priority queue according to the next three-dimensional map data to obtain an updated priority queue; The second backtracking module is used to backtrack the path of the update priority queue to obtain an updated optimized path.

9. The device according to claim 8, characterized in that The current three-dimensional map data includes: the motion data of the target mover and the motion data of the non-target mover; the adding module includes: A screening module, configured to screen the map node objects according to the candidate node objects adjacent to the starting point node object to obtain a selected node object; A first construction module is configured to construct the road segment loss data between the starting node object and the selected node object according to the starting node object, the selected node object, the motion data of the target mover, and the motion data of the non-target mover; An adding submodule is used to add the selected node object to a preset priority queue according to the road section loss data and the terminal node object to obtain a current priority queue.

10. The device according to claim 9, characterized in that The first building block includes: A first acquisition submodule is used to acquire the travel section of the selected node object and the starting node object to obtain the selected section; a screening submodule, configured to screen the motion data of the non-target movers according to the non-target movers traveling on the selected road section to obtain the motion data of the selected non-target movers; A second acquisition submodule is used to acquire the travel section length of the selected section to obtain a selected length; A third acquisition submodule is used to acquire the road section curvature of the selected road section to obtain a selected curvature; A fourth acquisition submodule is used to obtain a planned workstation distance, a maximum planned speed, and a planned mover speed between the selected node object and the starting node object; A construction submodule is used to construct the road section loss data based on the preset loss weight data, the selected length, the selected non-target mover motion data and the target mover motion data, the selected curvature, the workstation planning distance, the maximum planning speed and the mover planning speed.

11. The method according to claim 10, characterized in that The loss weight data includes: collision time loss weight, collision distance loss weight, longitudinal acceleration change rate loss weight, acceleration loss weight, curvature weight, position difference loss weight and speed loss weight; the selected non-target mover motion data includes: selected non-target mover motion speed; the target mover motion data includes: target mover motion speed, longitudinal acceleration change rate, acceleration; the construction submodule includes: a first constructing unit, configured to construct a collision distance according to the selected length, the motion speed of the non-target mover, and the motion speed of the target mover; a second constructing unit, configured to construct a collision time according to the collision distance, the motion speed of the non-target mover, and the motion speed of the target mover; a third constructing unit, configured to construct safety loss data according to the collision time, the collision distance, the collision time loss weight, and the collision distance loss weight; a fourth constructing unit, configured to construct stability loss data according to the longitudinal acceleration change rate, the longitudinal acceleration change rate loss weight, the acceleration, the acceleration loss weight, the target mover motion speed, the selected curvature, and the curvature weight; a fifth constructing unit, configured to construct efficiency loss data according to the position difference loss weight, the workstation planning distance, the maximum planning speed, and the mover planning speed; The sixth construction unit is used to construct the road section loss data according to the safety loss data, the stability loss data, and the efficiency loss data.

12. The device according to claim 9, characterized in that The adding submodule includes: An arranging unit, configured to arrange the selected node objects in ascending order according to the road section loss data of the selected node objects to obtain an ascending sequence of node objects; An adding unit is used to add the selected node object to the priority queue according to the ascending sequence of the node objects and the end node object to obtain the current priority queue.

13. The device according to claim 8, characterized in that The device further comprises: A search module, configured to search the map node object in the current priority queue to obtain a queue search result; wherein the queue search result indicates whether the map node object exists in the priority queue; The output module is configured to output path search failure information if the queue search result indicates that the map node object does not exist in the priority queue.

14. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the mover path optimization method according to any one of claims 1 to 7 when executing the computer program.

15. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the mover path optimization method according to any one of claims 1 to 7 is implemented.

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