Path planning method and device, electronic equipment and storage medium
By constructing a target dictionary and calculating the time cost in the underground roadway environment, the path planning is optimized, which solves the problems of low efficiency and poor safety of traditional algorithms in underground roadways, and realizes efficient and safe automatic driving of mine shuttle cars.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENHUA SHENDONG COAL GRP
- Filing Date
- 2025-11-21
- Publication Date
- 2026-06-05
AI Technical Summary
Traditional path planning algorithms are difficult to adapt to the complex environment of underground tunnels, resulting in low efficiency and poor safety of mine shuttle cars during automatic operation, and lack of high-precision dynamic environment path planning mechanisms.
By acquiring a map of the alleyway environment, adding drivable nodes and directed edges, constructing a target dictionary, calculating the time cost of straight lines and turns between nodes, and optimizing path planning based on the A* algorithm to reduce turning behavior.
It significantly shortens task completion time, improves path smoothness and driving efficiency, reduces computational complexity, and enhances the robustness and safety of path planning.
Smart Images
Figure CN122149508A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, and in particular to a path planning method, apparatus, electronic device and storage medium. Background Technology
[0002] With the advancement of intelligent and unmanned construction in coal mines, mining transportation equipment is gradually developing towards autonomous driving and intelligent scheduling. As a key piece of equipment in the underground coal transportation process, shuttle cars mainly undertake the task of transferring materials between the tunneling face and the transfer point. Traditional shuttle cars rely on manual driving, which is carried out in narrow operating environments with low visibility, high dust levels, and winding and complex road conditions and ventilation. Manual operation is not only labor-intensive and inefficient, but also poses high safety risks. Therefore, developing unmanned shuttle car systems for mining to achieve autonomous driving and intelligent scheduling has become an important direction for intelligent transportation technology in coal mines.
[0003] The environment of underground mine tunnels differs fundamentally from that of surface roads. Mine roads are typically narrow, have small turning radii, and exhibit significant gradient changes. They also contain complex factors such as water vapor, dust, and electromagnetic interference, making it difficult to directly apply traditional path planning algorithms based on high-precision maps. Furthermore, the underground traffic environment is highly dynamic, requiring simultaneous consideration of the coordination and obstacle avoidance of multiple devices such as tunneling machines and loaders. This places higher demands on the real-time performance and robustness of path planning algorithms. Existing path planning methods mostly employ fixed trajectories or manual remote control modes, lacking a high-precision path planning mechanism for dynamic environments, thus failing to achieve efficient and safe automated driving. Summary of the Invention
[0004] This application aims to at least partially address one of the technical problems in the related art.
[0005] Therefore, the first objective of this application is to propose a path planning method to achieve efficient and safe autonomous driving.
[0006] The second objective of this application is to propose a path planning device.
[0007] The third objective of this application is to propose an electronic device.
[0008] The fourth objective of this application is to provide a computer-readable storage medium.
[0009] The fifth objective of this application is to provide a computer program product.
[0010] To achieve the above objectives, a first aspect of this application proposes a path planning method, comprising: A first map of the alleyway environment is obtained, and drivable nodes and directed edges between nodes are added to the first map to obtain a second map, wherein the first map includes alleyway edge and obstacle information; A target dictionary is constructed based on the node information and directed edge information in the second map; The first time cost of straight-line travel and the second time cost of turning travel between nodes are obtained based on the target dictionary. Based on the first time cost and the second time cost, the target path for the shuttle to travel to the target node is determined.
[0011] To achieve the above objectives, a second aspect of this application provides a path planning apparatus, comprising: The first acquisition module is used to acquire a first map of the alleyway environment, and add drivable nodes and directed edges between nodes to the first map to obtain a second map, wherein the first map includes alleyway edge and obstacle information; The second acquisition module is used to construct a target dictionary based on the node information and directed edge information in the second map; The third acquisition module is used to acquire the first time cost of straight-line travel and the second time cost of turning travel between nodes according to the target dictionary; The planning module is used to determine the target path for the shuttle to travel to the target node based on the first time cost and the second time cost. To achieve the above objectives, a third aspect of this application provides an electronic device comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method described in the first aspect embodiment.
[0012] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method described in the first aspect embodiment.
[0013] To achieve the above objectives, a fifth aspect of this application provides a computer program product including a computer program that, when executed by a processor, implements the method described in the first aspect.
[0014] The path planning method, apparatus, electronic device, and storage medium provided in this application determine a first map of the tunnel environment and add nodes and directed edges to the first map to form a second map. Based on the second map, a target dictionary is constructed, which includes node information and directed edge information. Traversal is performed based on the information in the target dictionary, which effectively reduces the computational complexity of path planning. The first time cost of straight-line travel and the second time cost of turning travel between nodes are obtained according to the target dictionary. Path planning is performed based on the first time cost and the second time cost, which significantly reduces the turning behavior of the shuttle car during the task and greatly shortens the task completion time.
[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart illustrating a path planning method provided in an embodiment of this application; Figure 2 A flowchart illustrating another path planning method provided in an embodiment of this application; Figure 3 A schematic diagram of a second map provided in an embodiment of this application; Figure 4 This is a flowchart illustrating the logic of the A* algorithm based on the embodiments of this application. Figure 5 This is a schematic diagram of a path planning device provided in an embodiment of this application. Detailed Implementation
[0017] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.
[0018] The path planning method, apparatus, electronic device, and storage medium of this application are described below with reference to the accompanying drawings.
[0019] Figure 1 This is a flowchart illustrating a path planning method provided in an embodiment of this application. Figure 1 As shown, this path planning method includes the following steps: S101, obtain the first map of the alleyway environment, and add drivable nodes and directed edges between nodes to the first map to obtain the second map.
[0020] In some embodiments, multiple laser sensors on the shuttle car can be used to scan the entire tunnel environment to obtain a specific Simultaneous Localization and Mapping (SLAM) base map as a first map, wherein the first map includes tunnel edge and obstacle information.
[0021] Optionally, the first map can be saved and edited, and nodes and directed edges can be added to form a topological map, which is the second map in this embodiment. The second map includes nodes and directed edges between nodes. Optionally, the second map can be represented as... ,in, It is a set of nodes; It is a directed edge geometry, where each directed edge corresponds to a parent node and a child node. The directed edge points from the parent node to the child node, and the shuttle can move according to the direction of the directed edge.
[0022] In some embodiments, the node set of the second map may also include the coordinate information of each node in the second map and information such as whether it can turn. In this embodiment, the lower left corner of the second map is set as the origin coordinate (0,0), and the coordinates of each node are determined according to the distance between each node in the second map and the origin coordinate. The directed edge set may also include information such as the speed of the shuttle on the path and whether the path has a slope.
[0023] S102, construct the target dictionary based on the node information and directed edge information in the second map.
[0024] In this embodiment, the key of the dictionary is node information, and the value of the dictionary is directed edge information related to the node. After constructing the target dictionary, in subsequent path planning, the path can be traversed directly based on the information in the target dictionary, which effectively reduces the computational complexity of path planning.
[0025] S103, obtain the first time cost of straight-line travel and the second time cost of turning travel between nodes based on the target dictionary.
[0026] Optionally, the distance between two nodes can be determined based on their coordinates, and the time required for the two nodes to travel in a straight line can be determined based on the distance and the travel speed, serving as the first time cost. The travel speed can be obtained from pre-configured information.
[0027] Optionally, the required turning angle difference can be determined based on the current angle of the turning node and the angle after turning, and the time required for turning can be determined based on the angle difference and the angular velocity of turning as a second time cost, wherein the angular velocity of turning can be obtained based on pre-configured information.
[0028] S104, based on the first time cost and the second time cost, determine the target path for the shuttle to travel to the target node.
[0029] In some embodiments, the sum of the first time cost and the second time cost can be obtained and used as the total time cost. When determining the target path for the shuttle to travel to the target node, the path with the smallest total time cost is selected as the target path.
[0030] Understandably, we can traverse each node one by one, that is, start from the starting node where the shuttle is located, determine the time value of each node being traversed, and select the node with the smallest time value as the starting node for the next traversal, until the target node is reached and the target path is obtained.
[0031] In this embodiment, a first map of the tunnel environment is determined, and nodes and directed edges are added to the first map to form a second map. A target dictionary corresponding to the node information and directed edge information is constructed based on the second map. Traversal is performed based on the information in the target dictionary, which effectively reduces the computational complexity of path planning. The first time cost of straight-line travel and the second time cost of turning travel between nodes are obtained according to the target dictionary. Path planning is performed based on the first time cost and the second time cost, which significantly reduces the turning behavior of the shuttle car during the task and greatly shortens the task completion time.
[0032] Based on the above embodiments, Figure 2 This is a flowchart illustrating another path planning method provided in an embodiment of this application. Figure 2 As shown, this path planning method includes the following steps: S201, obtain the first map of the alleyway environment, and add drivable nodes and directed edges between nodes to the first map to obtain the second map.
[0033] For example, the second map after adding drivable nodes and directed edges between nodes is as follows: Figure 3 As shown.
[0034] In this application embodiment, the implementation method of step S201 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.
[0035] S202, construct the target dictionary based on the node information and directed edge information in the second map.
[0036] Optionally, the node information corresponding to each node can be used as the key, and the node information includes at least the node coordinates and node turning information; the directed edge information corresponding to the node can be obtained as the value, and the directed edge information includes at least the directed edge starting from the node and the adjacent nodes pointed to by the directed edge; and a target dictionary can be constructed based on the key-value pairs in the second map.
[0037] In this application embodiment, the implementation method of step S202 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.
[0038] S203, determine the coordinates and turning information of the nodes based on the node information in the target dictionary.
[0039] Optionally, the node turning information includes at least an indication of whether the node position can turn, and the turning angle when it can turn.
[0040] S204, obtain the shuttle's straight-line speed and shuttle's turning angular velocity.
[0041] In some embodiments, the shuttle's straight-line travel speed and shuttle's turning angular velocity can be pre-configured and stored in the target dictionary. In this embodiment, different travel speeds can be configured for paths with slopes and flat paths, and different turning angular velocities can also be configured for different turning angles to ensure more accurate path planning.
[0042] S205, determine the first time cost of straight-line travel between nodes based on the coordinates between nodes and the straight-line travel speed of the shuttle.
[0043] Optionally, the first-time cost can be expressed as:
[0044] in, This represents the first-time cost between node m and node n; Let m be the coordinates of node m; Let n be the coordinates of node n; The speed at which the shuttle travels in a straight line.
[0045] S206, in response to the instruction information indicating that the node can turn, determines the second time cost of turning and driving based on the turning angle, the target turning angle and the shuttle turning angular velocity.
[0046] Optionally, the absolute angle difference between the steering angle and the target steering angle can be obtained; based on the absolute angle difference and the shuttle's steering angular velocity, a second time cost for steering is determined, expressed as:
[0047] in, This represents the second time cost of node p performing a turning maneuver. Let be the target angle of node i, which is also the target turning angle; This is the initial angle of the current node p, which is also the turning angle; This refers to the angular velocity of the shuttle car's turning direction.
[0048] In some embodiments, in response to the indication information of the currently traversed node indicating that the node cannot turn, the directed edges that need to turn are removed according to the directed edge information of the currently traversed node. According to the remaining directed edges corresponding to the currently traversed node, the corresponding straight adjacent node is determined. The straight adjacent node does not have the second time cost of turning, that is, when the node is marked as not allowing turning, the feasibility of turning with that node is not searched.
[0049] S207, based on the first time cost and the second time cost, determine the target path for the shuttle to travel to the target node.
[0050] Alternatively, path planning can be performed based on the A* algorithm to obtain the shortest path from the starting node to the target node as the target path.
[0051] In some embodiments, the location of the shuttle can be obtained, and a match can be made in the target dictionary based on the location of the shuttle to obtain the node that is closest to the location of the shuttle, and the node is determined as the starting node corresponding to the shuttle.
[0052] Optionally, two lists can be created during traversal: an openlist and a closedlist. The openlist stores nodes to be expanded, i.e., nodes whose inclusion in the shortest path is not yet determined. The closedlist stores expanded nodes, i.e., nodes that have been calculated and determined not to be included in the shortest path. This avoids processing the same node repeatedly and improves algorithm efficiency.
[0053] At the beginning of the traversal, the starting node corresponding to the shuttle can be added to the blacklist to avoid repeatedly passing through the current position of the shuttle during path planning, thereby improving the efficiency of path search and preventing invalid loops; the starting node corresponding to the shuttle is used as the current traversal node and added to the openlist for traversal analysis.
[0054] Optionally, the neighboring nodes of the currently traversed node can be determined based on the directed edge information in the target dictionary. That is, the node pointed to by each directed edge in the directed edge corresponding to the currently traversed node is the neighboring node of the currently traversed node.
[0055] Optionally, candidate nodes among the adjacent nodes can be determined based on the first time cost and the second time cost between the current traversed node and each adjacent node. The process of obtaining the first time cost and the second time cost will not be repeated here.
[0056] In some embodiments, the sum of the first time cost and the second time cost corresponding to adjacent nodes can be calculated to obtain the third time cost, which is expressed as:
[0057] in, As a third time cost; For the currently traversed node With neighboring nodes The initial cost between them; For the currently traversed node With neighboring nodes The second time cost between them.
[0058] Furthermore, the fourth time cost of traveling in a straight line and the fifth time cost of turning between the current traversed node and the target node can be summed to obtain the sixth time cost, which is expressed as:
[0059] in, For the cost of the sixth time; The coordinates of the target node; This is the cost of the fourth time. For the fifth time cost; The target angle is the target angle of the target node. In this embodiment, it is assumed that the target angle of the target node is the same as the angle of its corresponding previous node.
[0060] The target time cost is obtained by summing the third and sixth time costs. The adjacent nodes that minimize the target time cost are identified as candidate nodes.
[0061] Furthermore, after determining the candidate node, the traversal continues with the candidate node as the current traversal node until the target node is reached. The target path is obtained by backtracking through the parent node. If the current traversal node is not the target node, the node is moved into the closedlist and the adjacent nodes of the current node are traversed.
[0062] In some embodiments, during the traversal process, it can be determined whether the neighboring nodes of the currently traversed node are already in the openlist. If the neighboring node is not in the openlist, the neighboring node is added to the openlist and the traversal continues. If the neighboring node is in the openlist, it means that the neighboring node has been found through a path in the previous traversal process, but now a path with a lower cost may have been found. In this case, the cost of the neighboring node is updated to the lower cost of the new path.
[0063] For example, suppose there is a path 1 that is A → B → D and a path 2 that is A → C → D. The total cost of path 1 is 6 and the total cost of path 2 is 4. Although node D has been discovered through path 1 and exists in the openlist, the cost of path 2 is smaller. Therefore, the information of node D will be updated, the corresponding total cost will be changed to 4, and its parent node will be changed from B to C, ensuring that the final backtracked target path is the path with the minimum cost. Furthermore, after obtaining the target path, the total time cost of the target path can also be obtained. Specifically, the total time cost of the target path can be expressed as:
[0064] in, This represents the total time cost of the target path.
[0065] In this embodiment, a second map is acquired, and a target dictionary is constructed based on the second map. This approach is well-suited for various scenarios, allowing for changes in the target dictionary as the environment or actual needs evolve. This addresses a variety of complex scenarios, reducing the complexity of path planning. The target dictionary is used to obtain the coordinates and turning information of nodes, as well as the shuttle's straight-line speed and turning angular velocity. Based on the coordinates between nodes and the shuttle's straight-line speed, the first time cost of straight-line travel between nodes is determined. When a node can turn, the second time cost of turning is determined based on the turning angle, the target turning angle, and the shuttle's turning angular velocity. The total target time cost is determined by the first time cost of straight-line travel and the second time cost of turning. This allows for the traversal of the target path from the shuttle to the target node. By incorporating turning time into the path planning algorithm, the turning behavior of the shuttle during task execution is significantly reduced, greatly shortening the task completion time and improving path smoothness and travel efficiency.
[0066] Based on the above embodiments, Figure 4As shown in the flowchart of the A* algorithm in this application embodiment, after the A* algorithm starts traversing, the node corresponding to the shuttle's position is added to the blacklist, and an openlist and a closedlist are created. The starting node of the shuttle's position is added to the openlist as the current traversal node. It is determined whether the current traversal node is the target node. If it is the target node, the traversal ends. If the current traversal node is not the target node, the openlist set is traversed to find the node with the minimum time cost as the candidate node, and the candidate node is used as the new current traversal node. The current traversal node is moved from the openlist to the closedlist, and all nodes with the minimum time cost are searched. The system uses the current traversed node as the starting point for directed edges, and the shuttle angle remains unchanged at the target node. It calculates the target time cost of the adjacent nodes corresponding to the directed edges, and checks whether the adjacent nodes already exist in the open list. If they do, the target time cost of the adjacent nodes is updated to a smaller time cost and traversal continues. If they do not exist in the open list, the adjacent nodes are added to the open list for analysis. The system checks whether the current traversed node is the target node until the target node is reached. Based on the current traversed node, the target path is obtained by backtracking the parent node. This significantly reduces the turning behavior of the shuttle during task execution, greatly shortens the task completion time, and has better performance.
[0067] The path planning method disclosed in this embodiment is verified by comparing it with the A* algorithm and Dijkstra's algorithm in the prior art, and verifying the advantages of this algorithm in terms of the number of turns, task completion time and computation time.
[0068] A test map consisting of 64 nodes is constructed. The shuttle starts from the starting node and randomly selects 10 nodes to perform movement tasks in sequence. The target node of the previous movement task becomes the starting node of the next movement task, for a total of 10 movement tasks. The average number of turns, average task completion time, and average path calculation time of different algorithms in these 10 movement tasks are recorded.
[0069] After random selection, the 10 movement tasks are: 50→23, 23→47, 47→5, 5→31, 31→12, 12→58, 58→3, 3→40, 40→19, 19→61. The paths obtained by each algorithm through simulation experiments can be intuitively seen to be smoother than the improved A* algorithm. The specific data of each algorithm are shown in Table 1. Although the computation time of the improved A* algorithm in this embodiment is longer than that of the traditional A* algorithm, its overall performance is better.
[0070] Table 1
[0071] To implement the above embodiments, this application also proposes a path planning device.
[0072] Figure 5 This is a schematic diagram of a path planning device provided in an embodiment of this application. Figure 5 As shown, the path planning device 500 includes: The first acquisition module 501 is used to acquire a first map of the alleyway environment, and add drivable nodes and directed edges between nodes to the first map to obtain a second map, wherein the first map includes alleyway edge and obstacle information; The second acquisition module 502 is used to construct a target dictionary based on the node information and directed edge information in the second map; The third acquisition module 503 is used to acquire the first time cost of straight-line travel and the second time cost of turning travel between nodes according to the target dictionary; Planning module 504 is used to determine the target path for the shuttle to travel to the target node based on the first time cost and the second time cost. Furthermore, in one possible implementation of this application embodiment, the second acquisition module 502 is used for: Each node's corresponding node information is used as the key, and the node information includes at least the node coordinates and node turning information. Obtain the directed edge information corresponding to the node as the value. The directed edge information includes at least the directed edge originating from the node and the adjacent nodes pointed to by the directed edge. Construct a target dictionary based on the key-value pairs in the second map.
[0073] Furthermore, in one possible implementation of this application embodiment, the third acquisition module 503 is used for: The coordinates and turning information of the node are determined based on the node information in the target dictionary. The turning information includes at least an indication of whether the node position can be turned, and the turning angle when it can be turned. Obtain the shuttle's straight-line speed and shuttle's turning angular velocity; The first time cost of straight-line travel between nodes is determined based on the coordinates between nodes and the straight-line travel speed of the shuttle. In response to the instruction information indicating that the node can turn, the second time cost of turning is determined based on the turning angle, the target turning angle, and the shuttle turning angular velocity.
[0074] Furthermore, in one possible implementation of this application embodiment, the third acquisition module 503 is used for: Obtain the absolute difference between the steering angle and the target steering angle; The second time cost of turning is determined based on the absolute difference in angle and the angular velocity of the shuttle.
[0075] Furthermore, in one possible implementation of this application embodiment, the planning module 504 is used for: Get the location of the shuttle car, match it in the target dictionary based on the location of the shuttle car, and determine the starting node corresponding to the shuttle car as the current traversal node; The adjacent nodes of the currently traversed node are determined based on the directed edge information in the target dictionary; Based on the first and second time costs between the current traversed node and each adjacent node, determine the candidate nodes among the adjacent nodes; Continue traversing with the candidate node as the current traversal node until the target node is reached, thus obtaining the target path.
[0076] Furthermore, in one possible implementation of this application embodiment, the planning module 504 is used for: The third time cost is obtained by summing the first and second time costs corresponding to adjacent nodes. The sixth time cost is obtained by summing the fourth time cost of traveling in a straight line and the fifth time cost of turning between the current traversed node and the target node. The target time cost is obtained by summing the third time cost and the sixth time cost. The adjacent nodes that minimize the target time cost are identified as candidate nodes.
[0077] Furthermore, in one possible implementation of this application embodiment, the planning module 504 is also used for: In response to the indication information of the currently traversed node indicating that the node cannot be turned, the directed edges that need to be turned are removed based on the directed edge information of the currently traversed node. Based on the remaining directed edges corresponding to the currently traversed node, determine the corresponding straight-line adjacent node. The target time cost of the straight-line adjacent node does not include the time cost of turning and traveling.
[0078] It should be noted that the foregoing explanation of the path planning method embodiment also applies to the path planning device of this embodiment, and will not be repeated here.
[0079] In this embodiment, a second map is obtained, and a target dictionary is constructed based on the second map. This method is well-suited for various scenarios and can be modified according to changes in the environment or actual needs to cope with various complex scenarios, reducing the complexity of path planning. The coordinates and turning information of nodes are obtained from the target dictionary, and the straight-line speed and turning angular velocity of the shuttle are obtained. Based on the coordinates between nodes and the straight-line speed of the shuttle, the first time cost of straight-line travel between nodes is determined. When a node can turn, the second time cost of turning is determined based on the turning angle, the target turning angle, and the turning angular velocity of the shuttle. The total target time cost is determined by the first time cost of straight-line travel and the second time cost of turning, thereby traversing to obtain the target path of the shuttle to the target node. By introducing turning time into the path planning algorithm, the turning behavior of the shuttle during task execution is significantly reduced, the task completion time is greatly shortened, and the path smoothness and driving efficiency are improved.
[0080] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.
[0081] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.
[0082] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0083] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.
[0084] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.
[0085] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0086] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0087] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.
[0088] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0089] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0090] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0091] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0092] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.
Claims
1. A path planning method, characterized in that, The method includes: A first map of the alleyway environment is obtained, and drivable nodes and directed edges between nodes are added to the first map to obtain a second map, wherein the first map includes alleyway edge and obstacle information; A target dictionary is constructed based on the node information and directed edge information in the second map; The first time cost of straight-line travel and the second time cost of turning travel between nodes are obtained based on the target dictionary. Based on the first time cost and the second time cost, the target path for the shuttle to travel to the target node is determined.
2. The method according to claim 1, characterized in that, The construction of the target dictionary based on the node information and directed edge information in the second map includes: Each node's corresponding node information is used as a key, and the node information includes at least node coordinates and node turning information; Obtain the directed edge information corresponding to the node as a value. The directed edge information includes at least the directed edge originating from the node and the adjacent nodes pointed to by the directed edge. Construct a target dictionary based on the key-value pairs in the second map.
3. The method according to claim 2, characterized in that, The step of obtaining the first time cost of straight-line travel and the second time cost of turning travel between nodes according to the target dictionary includes: The coordinates and turning information of the node are determined based on the node information in the target dictionary. The turning information includes at least an indication of whether the node position can be turned, and the turning angle when it can be turned. Obtain the shuttle's straight-line speed and shuttle's turning angular velocity; The first time cost of straight-line travel between nodes is determined based on the coordinates between nodes and the straight-line travel speed of the shuttle. In response to an indication that the node can turn, a second time cost for turning is determined based on the turning angle, the target turning angle, and the shuttle turning angular velocity.
4. The method according to claim 3, characterized in that, The determination of the second time cost for turning and driving based on the steering angle, the target steering angle, and the shuttle car steering angular velocity includes: Obtain the absolute angle difference between the steering angle and the target steering angle; The second time cost of turning is determined based on the absolute difference in angle and the angular velocity of the shuttle.
5. The method according to any one of claims 1-4, characterized in that, Determining the target path for the shuttle to reach the target node based on the first time cost and the second time cost includes: Get the location of the shuttle car, match it in the target dictionary based on the location of the shuttle car, and determine the starting node corresponding to the shuttle car as the current traversal node; The adjacent nodes of the currently traversed node are determined based on the directed edge information in the target dictionary; Based on the first time cost and the second time cost between the current traversed node and each of the adjacent nodes, candidate nodes among the adjacent nodes are determined; The candidate node is used as the current traversal node to continue traversing until the target node is reached, thus obtaining the target path.
6. The method according to claim 5, characterized in that, The step of determining candidate nodes among the neighboring nodes based on the first time cost and the second time cost between the currently traversed node and each of the neighboring nodes includes: The third time cost is obtained by summing the first time cost and the second time cost corresponding to the adjacent nodes. The sixth time cost is obtained by summing the fourth time cost of traveling in a straight line and the fifth time cost of turning between the current traversed node and the target node. The target time cost is obtained by summing the third time cost and the sixth time cost. The neighboring node corresponding to the minimum target time cost is determined as the candidate node.
7. The method according to claim 6, characterized in that, The method further includes: In response to the indication information of the currently traversed node indicating that the node cannot be turned, the directed edges that need to be turned are removed according to the directed edge information of the currently traversed node. Based on the remaining directed edges corresponding to the currently traversed node, determine the corresponding straight adjacent node. The target time cost of the straight adjacent node does not include the time cost of turning and driving.
8. A path planning device, characterized in that, include: The first acquisition module is used to acquire a first map of the alleyway environment, and add drivable nodes and directed edges between nodes to the first map to obtain a second map, wherein the first map includes alleyway edge and obstacle information; The second acquisition module is used to construct a target dictionary based on the node information and directed edge information in the second map; The third acquisition module is used to acquire the first time cost of straight-line travel and the second time cost of turning travel between nodes according to the target dictionary; The planning module is used to determine the target path for the shuttle to travel to the target node based on the first time cost and the second time cost.
9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.
10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.