Downhole path planning method and apparatus, and device and storage medium

Abstract

A downhole path planning method and apparatus, and a device and a storage medium. The method comprises the steps of: generating a vehicle traveling region boundary by combining a vehicle traveling region, which is provided by a perception sensor, with a field of view of the sensor (S101); performing conversion processing on the vehicle traveling region boundary, so as to generate a grid map (S102); and on the basis of the grid map, determining a starting point and a destination point of a vehicle, using a path search algorithm to generate path control points, and performing fitting on the path control points, so as to plan a traveling path (S103). In the method, the problem of there being limitations due to a dead zone during downhole operation can be effectively solved, and the time for generating a path can also be reduced, thereby improving a path planning rate.

Description

A method, apparatus, equipment and storage medium for downhole path planning Technical Field

[0001] This invention relates to the field of autonomous driving technology, and in particular to a method, apparatus, device, and storage medium for downhole path planning. Background Technology

[0002] The industry's autonomous driving path planning is mainly applied to structured road scenarios such as highways and cities. The planning technology used is not entirely suitable for unstructured roads underground, and does not take into account the characteristics of narrow underground space, uneven mine walls, and irregular road edges.

[0003] In existing technologies, road boundaries can generally be obtained and drivable paths planned based on information such as maps, perception, and positioning. However, the limitations imposed by perception blind spots are not considered. When generating paths, random sampling is performed from the vehicle's starting point, and the sampled points are connected to generate the path. This method requires a sufficient number of sampled points; as the number of sampled points increases, the time consumption increases, leading to a decrease in path planning speed.

[0004] Therefore, how to plan routes and improve the speed of route planning is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] The main objective of this invention is to provide a downhole path planning method, apparatus, equipment, and storage medium that can effectively solve the problem of blind zone limitations during downhole operations, and also reduce path generation time and improve path planning speed.

[0006] In a first aspect, this application provides a downhole path planning method, wherein the method includes the following steps:

[0007] The vehicle driving area provided by the perception sensor is combined with the sensor's field of view to generate the boundary of the vehicle driving area.

[0008] The boundaries of the vehicle's driving area are transformed to generate a raster map;

[0009] Based on a grid map, the vehicle's starting point and target point are determined, and a path search algorithm is used to generate path control points. The path control points are then fitted to plan the driving route.

[0010] In conjunction with the first aspect mentioned above, as an optional implementation method, the point cloud information collected by the sensing sensor is decoded to generate boundary point cloud information;

[0011] The boundary point cloud information is combined with the field of view of the sensor to fill in the blind spots of the vehicle and generate single-layer point cloud data.

[0012] The single-layer point cloud data is filtered to obtain the boundary of the vehicle driving area.

[0013] In conjunction with the first aspect mentioned above, as an optional implementation, a grid map is generated using a breadth-first search algorithm based on the boundaries of the vehicle's driving area.

[0014] In conjunction with the first aspect mentioned above, as an optional implementation method, the starting point and target point of the vehicle are determined in the grid map;

[0015] The initial radius is determined based on the vehicle width and calibration parameters, and the annulus is determined with the starting point and the target point as the center respectively;

[0016] Control the rings to move towards each other and search in opposite directions, and determine whether the rings collide with the wall;

[0017] If not, store the center point of the ring that does not collide with the wall, and use it as the path control point.

[0018] If so, calculate the collision value and blind zone value of the current center in multiple directions, and after iterating the ring towards the point of maximum gradient in multiple directions, move the center or reduce the radius until the ring does not collide with the wall, and store the center of the ring that does not collide with the wall as a control point.

[0019] In conjunction with the first aspect mentioned above, as an optional implementation method, it is determined whether the circles moving towards each other from the starting point and the target point meet.

[0020] If they meet, the search ends; if they do not meet, the center of the circle is moved and they move towards each other until they meet.

[0021] In conjunction with the first aspect mentioned above, as an optional implementation method, the control points are fitted using a fifth-order polynomial fitting algorithm to generate a planned path.

[0022] Secondly, this application provides a downhole path planning device, which includes:

[0023] The processing module combines the vehicle driving area given by the perception sensor with the sensor's field of view to generate the boundary of the vehicle driving area.

[0024] The generation module is used to transform the boundary of the vehicle driving area and generate a raster map;

[0025] The planning module is used to determine the vehicle's starting point and target point based on a grid map, and to generate path control points using a path search algorithm, and to fit the path control points to plan the driving path.

[0026] Thirdly, this application also provides an electronic device, the electronic device comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the method described in any one of the first aspects.

[0027] Fourthly, this application also provides a computer-readable storage medium storing computer program instructions that, when executed by a computer, cause the computer to perform the method described in any of the first aspects.

[0028] This application provides a downhole path planning method, apparatus, device, and storage medium. The method includes the following steps: combining the vehicle driving area given by a sensing sensor with the sensor's field of view to generate a vehicle driving area boundary; performing a transformation process on the vehicle driving area boundary to generate a grid map; determining the vehicle's starting point and target point based on the grid map, and using a path search algorithm to generate path control points, and fitting the path control points to plan the driving path. This application can effectively solve the problem of blind zone limitations during downhole operations, and can also reduce the path generation time and improve the path planning speed.

[0029] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0030] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0031] Figure 1 is a flowchart of a downhole path planning method provided in an embodiment of this application;

[0032] Figure 2 is a schematic diagram of a downhole path planning device provided in an embodiment of this application;

[0033] Figure 3 is a schematic diagram of path search provided in the embodiments of this application;

[0034] Figure 4 is a schematic diagram of the circular search provided in the embodiment of this application;

[0035] Figure 5 is a schematic diagram of an electronic device provided in an embodiment of this application;

[0036] Figure 6 is a schematic diagram of a computer-readable program medium provided in an embodiment of this application. Detailed Implementation

[0037] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0038] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the drawings represent functional entities and do not necessarily correspond to physically or logically independent entities.

[0039] This application provides a downhole path planning method, apparatus, device, and storage medium, which can effectively solve the problem of blind zone limitation during downhole operations, and can also reduce the path generation time and improve the path planning rate.

[0040] To achieve the aforementioned technical effects, the general concept of this application is as follows:

[0041] A downhole path planning method, the method comprising the following steps:

[0042] S101: Combine the vehicle driving area given by the perception sensor with the sensor's field of view to generate the boundary of the vehicle driving area.

[0043] S102: Perform conversion processing on the boundary of the vehicle driving area to generate a raster map.

[0044] S103: Based on the grid map, determine the vehicle's starting point and target point, and use a path search algorithm to generate path control points. Then, fit the path control points to plan the driving path.

[0045] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0046] Referring to Figure 1, which is a flowchart of a downhole path planning method provided by the present invention, the method includes the following steps:

[0047] Step S101: Combine the vehicle driving area given by the perception sensor with the sensor's field of view to generate the boundary of the vehicle driving area.

[0048] Specifically, the point cloud information collected by the perception sensor is decoded to generate boundary point cloud information; the boundary point cloud information is combined with the field of view of the sensor to fill in the blind spots of the vehicle driving and generate single-layer point cloud data; the single-layer point cloud data is filtered to obtain the boundary of the vehicle driving area.

[0049] To illustrate this more clearly, the point cloud information collected by sensors is decoded to generate usable boundary information for planning. Based on this boundary information (the boundary points of the drivable area, i.e., the boundary of the underground mine wall) and the sensor's field of view (front radar field of view: 180 degrees; rear radar field of view: 120 degrees), blind spots are filled in (i.e., searching counter-clockwise for intersections with the boundary from the right front of the vehicle based on the sensor's angle), generating single-layer point cloud data to ultimately obtain the boundary points of the drivable area. The single-layer point cloud data from the front and rear radar field of view is then filtered to determine the drivable area boundary. It should be noted that the boundary is three-dimensional; however, by using the intersections with the vehicle, it can be filtered into two-dimensional data, leaving only the single-layer point cloud information.

[0050] Step S102: Convert the boundary of the vehicle driving area to generate a raster map.

[0051] Specifically, a raster map is generated using a breadth-first search algorithm based on the boundaries of the vehicle's driving area. It's important to explain that breadth-first search (BFS) is an algorithm used to traverse or search a tree or graph. It starts from the root node (or any node) and expands outwards until the target node is found or the entire graph has been traversed. BFS maintains a queue data structure during the search process, enqueuing all adjacent nodes and processing them one by one. This search method is particularly suitable for situations where nodes are relatively close together. It's also important to note that a raster map is a raster data file obtained by processing existing paper topographic maps using a computer. After scanning and digitizing, each topographic map undergoes geometric correction, color correction, and data compression to ultimately form a raster dataset that maintains consistency with the national basic scale topographic map in terms of content, geometric accuracy, and color.

[0052] Step S103: Based on the grid map, determine the vehicle's starting point and target point, and use a path search algorithm to generate path control points. Then, fit the path control points to plan the driving path.

[0053] Specifically, the starting and destination points of the vehicle are determined in the grid map;

[0054] The initial radius is determined based on the vehicle width and calibration parameters, and the annulus is determined with the starting point and the target point as the center respectively;

[0055] Control the rings to move towards each other and search in opposite directions, and determine whether the rings collide with the wall;

[0056] If not, store the center point of the ring that does not collide with the wall, and use it as the path control point.

[0057] If so, calculate the collision value and blind zone value of the current center in multiple directions, and after iterating the ring towards the point of maximum gradient in multiple directions, move the center or reduce the radius until the ring does not collide with the wall, and store the center of the ring that does not collide with the wall as a control point.

[0058] To illustrate this with an example, let's define the starting and ending points: Starting from the vehicle's location, mark the target point (endpoint) within the drivable area. For instance, on a grid map, set points A and B. When the vehicle is moving in the direction of AB, A and B are within the sensor's field of view. The midpoint of AB is the target point (endpoint). It's important to explain that point B is not chosen as the end point because both A and B are points where the vehicle can be sensed and intersect the mine wall. If point B were the starting point, the vehicle would be targeting points on the wall, leading to a collision. Therefore, setting the midpoint of AB as the target point prevents the vehicle from crashing into the wall.

[0059] A search loop is generated, searching simultaneously in both the starting and ending directions. Using the starting and ending points as radii, and an initial radius of vehicle width + 'a' (where 'a' is a calibrable parameter), the loops are determined. These loops move simultaneously towards each other, searching in opposite directions. The center point of the loop that avoids collisions is stored. The center of this non-collision loop is used as the path control point. When a search loop collides with a wall, the collision values ​​(the center point of the loop when it touches the wall during the search) and blind zone values ​​(the center point of the loop when it coincides with the blind zone) in the eight directions are calculated. The loop iterates towards the point with the maximum gradient in the eight directions (the four sides and four corners of the grid), moving the center or reducing the radius until the loop avoids collisions with walls. The non-collision center is then stored as a control point. A fifth-order polynomial fitting algorithm is used to fit these control points, generating the planned path.

[0060] It's important to explain that the bidirectional circle search algorithm is a strategy to optimize the search process. It searches simultaneously from two directions: one starting from the starting point and the other from the target point. A breadth-first search is performed simultaneously from both the start and end points. If the fronts of the two searches meet, a feasible solution is considered to have been found. This method involves adding the start and target nodes to queues and marking them, then alternately expanding the nodes in both directions until a meeting point is found.

[0061] In one embodiment, it is determined whether the circles in the directions of the starting point and the target point meet while moving towards each other; if they meet, the search ends; if they do not meet, the center of the circle is moved and they move towards each other until they meet.

[0062] Understandably, the approach involves combining sensor-acquired information (point cloud information of the drivable area boundary) with the sensor's field of view to obtain usable boundary information for planning (the boundary of the underground mine wall), and then converting this boundary information into a raster map. Based on the raster map, a bidirectional circle search algorithm is employed to plan a collision-free path that satisfies vehicle dynamics constraints, thus solving the planning challenges faced in special underground mining scenarios.

[0063] Considering the complex conditions underground, blind spots are taken into account at turns. A grid map is generated based on sensor information. The starting and target points are then determined based on the grid map and vehicle information. A bidirectional search algorithm is used to quickly identify control points, smooth the control points, and generate the target trajectory in a relatively short time.

[0064] In summary, this application provides a downhole path planning method, apparatus, device, and storage medium. The method includes the following steps: combining the vehicle driving area provided by a sensing sensor with the sensor's field of view to generate a vehicle driving area boundary; performing a transformation process on the vehicle driving area boundary to generate a grid map; determining the vehicle's starting point and target point based on the grid map, and using a path search algorithm to generate path control points, and fitting the path control points to plan the driving path. This application can effectively solve the problem of blind zone limitations during downhole operations and can also reduce path generation time and improve path planning speed.

[0065] Referring to Figure 2, which is a schematic diagram of a downhole path planning device provided by the present invention, the device includes:

[0066] Processing module 201: It is used to combine the vehicle driving area given by the perception sensor with the sensor's field of view to generate the boundary of the vehicle driving area.

[0067] Generation module 202: It is used to transform the boundary of the vehicle driving area and generate a raster map.

[0068] Planning module 203: It is used to determine the vehicle's starting point and target point based on a grid map, and to generate path control points using a path search algorithm, and to fit the path control points to plan the driving path.

[0069] Furthermore, in one possible implementation, the processing module is also used to decode the point cloud information collected by the sensing sensor to generate boundary point cloud information.

[0070] The boundary point cloud information is combined with the field of view of the sensor to fill in the blind spots of the vehicle and generate single-layer point cloud data.

[0071] The single-layer point cloud data is filtered to obtain the boundary of the vehicle driving area.

[0072] Furthermore, in one possible implementation, the generation module is also used to generate a raster map based on the boundaries of the vehicle driving area using a breadth-first search algorithm.

[0073] Furthermore, in one possible implementation, the planning module is also used to determine the vehicle's starting point and target point in the grid map;

[0074] The initial radius is determined based on the vehicle width and calibration parameters, and the annulus is determined with the starting point and the target point as the center respectively;

[0075] Control the rings to move towards each other and search in opposite directions, and determine whether the rings collide with the wall;

[0076] If not, store the center point of the ring that does not collide with the wall, and use it as the path control point.

[0077] If so, calculate the collision value and blind zone value of the current center in multiple directions, and after iterating the ring towards the point of maximum gradient in multiple directions, move the center or reduce the radius until the ring does not collide with the wall, and store the center of the ring that does not collide with the wall as a control point.

[0078] Furthermore, in one possible implementation, the processing module is also used to determine whether the circular paths of the starting point and the target point meet as they travel towards each other.

[0079] If they meet, the search ends; if they do not meet, the center of the circle is moved and they move towards each other until they meet.

[0080] Furthermore, in one possible implementation, the planning module is also used to fit the control points using a fifth-order polynomial fitting algorithm to generate a planned path.

[0081] Referring to Figure 3, which is a schematic diagram of the path search provided by the present invention, as shown in Figure 3:

[0082] Determine the starting and target points on the grid map, using the starting and ending points as the center points, with an initial radius of: vehicle width + a (a is a calibrable parameter). Define the rings, and have the rings move towards each other to search. Determine if the rings collide with the wall. If not, store the center point of the current ring that does not collide with the wall, and use the center of the ring that does not collide with the wall as the path control point. If it does collide with the wall, calculate the collision value and blind zone value of the current center in 8 directions. Iterate the ring towards the point of maximum gradient in 8 directions, move the center or reduce the radius, and continue to return to the wall collision judgment until there is no collision with the wall. Then store the center of the ring that does not collide with the wall as the control point.

[0083] After storing the center of the circle that does not collide with the wall as the control point, it is determined whether the two circles meet. If they do, the process ends; otherwise, their respective centers move towards each other, i.e., the starting center moves towards the ending center, and the ending center moves towards the starting center.

[0084] For unstructured roads and irregular mine walls in underground mines, the drivable area boundary is generated by combining the drivable area given by perception with the sensor's field of view, thus solving the problem of limited blind spots on curves; a bidirectional circular iterative search algorithm is adopted to improve the accuracy and efficiency of path generation.

[0085] Referring to Figure 4, which illustrates the path search provided by this invention: Starting from the vehicle's location, target points are marked within the drivable area. Using the start and end points as points, an initial radius of vehicle width + 'a' (where 'a' is a calibrable parameter) is established, forming a ring. These rings simultaneously move towards each other for the search, as shown in Figure 4. The center point of the ring that avoids collisions with walls (as shown in Figure 4, the gray area represents the wall, and the white area represents the drivable area) is stored, and this center serves as the path control point. When a search circle collides with a wall, the collision values ​​and blind zone values ​​in eight directions of the current center are calculated. The ring iterates towards the point of maximum gradient in each of the eight directions, moving the center or reducing the radius until it avoids collisions with walls. The center of the non-collision ring is then stored as the control point. The rings in the start and end directions move towards each other until they meet.

[0086] The electronic device 500 according to this embodiment of the present invention will now be described with reference to FIG5. The electronic device 500 shown in FIG5 is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0087] As shown in Figure 5, the electronic device 500 is presented in the form of a general-purpose computing device. The components of the electronic device 500 may include, but are not limited to: at least one processing unit 510, at least one storage unit 520, and a bus 530 connecting different system components (including storage unit 520 and processing unit 510).

[0088] The storage unit stores program code that can be executed by the processing unit 510, causing the processing unit 510 to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of the present invention.

[0089] Storage unit 520 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 521 and / or cache memory 522, and may further include a read-only memory (ROM) 523.

[0090] Storage unit 520 may also include a program / utility 524 having a set (at least one) program module 525, such program module 525 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0091] Bus 530 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0092] Electronic device 500 can also communicate with one or more external devices (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 500, and / or any device that enables electronic device 500 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 550. Furthermore, electronic device 500 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 560. As shown, network adapter 560 communicates with other modules of electronic device 500 via bus 530. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0093] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0094] According to the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0095] Referring to Figure 6, a program product 600 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0096] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0097] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0098] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0099] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0100] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0101] In summary, this application provides a downhole path planning method, apparatus, device, and storage medium. The method includes the following steps: combining the vehicle driving area provided by a sensing sensor with the sensor's field of view to generate a vehicle driving area boundary; performing a transformation process on the vehicle driving area boundary to generate a grid map; determining the vehicle's starting point and target point based on the grid map, and using a path search algorithm to generate path control points, and fitting the path control points to plan the driving path. This application can effectively solve the problem of blind zone limitations during downhole operations and can also reduce path generation time and improve path planning speed.

[0102] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

Claims

1. A method for downhole path planning, characterized in that, include: The vehicle driving area provided by the perception sensor is combined with the sensor's field of view to generate the boundary of the vehicle driving area. The boundaries of the vehicle's driving area are transformed to generate a raster map; Based on a grid map, the vehicle's starting point and target point are determined, and a path search algorithm is used to generate path control points. The path control points are then fitted to plan the driving route.

2. The method according to claim 1, characterized in that, The step of combining the vehicle driving area provided by the sensing sensor with the sensor's field of view to generate the vehicle driving area boundary includes: The point cloud information collected by the sensing sensor is decoded to generate boundary point cloud information; The boundary point cloud information is combined with the field of view of the sensor to fill in the blind spots of the vehicle and generate single-layer point cloud data. The single-layer point cloud data is filtered to obtain the boundary of the vehicle driving area.

3. The method according to claim 1, characterized in that, The step of transforming the boundary of the vehicle driving area to generate a raster map includes: A raster map is generated based on the boundaries of the vehicle's driving area using a breadth-first search algorithm.

4. The method according to claim 1, characterized in that, The process of determining the vehicle's starting and destination points based on a grid map and generating path control points using a path search algorithm includes: The vehicle's starting and destination points are determined in the grid map; The initial radius is determined based on the vehicle width and calibration parameters, and the annulus is determined with the starting point and the target point as the center respectively; Control the rings to move towards each other and search in opposite directions, and determine whether the rings collide with the wall; If not, store the center point of the ring that does not collide with the wall, and use it as the path control point. If so, calculate the collision value and blind zone value of the current center in multiple directions, and after iterating the ring towards the point of maximum gradient in multiple directions, move the center or reduce the radius until the ring does not collide with the wall, and store the center of the ring that does not collide with the wall as a control point.

5. The method according to claim 4, characterized in that, include: Determine whether the circles moving towards each other from the starting point and the target point meet; If they meet, the search ends; If they do not meet, move the center of the circle and move towards each other until they meet.

6. The method according to claim 1, characterized in that, The process of fitting the path control points to plan the driving path includes: The control points are fitted using a fifth-order polynomial fitting algorithm to generate a planned path.

7. A downhole path planning device, characterized in that, include: The processing module combines the vehicle driving area given by the perception sensor with the sensor's field of view to generate the boundary of the vehicle driving area. The generation module is used to transform the boundary of the vehicle driving area and generate a raster map; The planning module is used to determine the vehicle's starting point and target point based on a grid map, and to generate path control points using a path search algorithm, and to fit the path control points to plan the driving path.

8. The apparatus according to claim 7, characterized in that: The processing module is also used to decode the point cloud information collected by the sensing sensor and generate boundary point cloud information; The boundary point cloud information is combined with the field of view of the sensor to fill in the blind spots of the vehicle and generate single-layer point cloud data. The single-layer point cloud data is filtered to obtain the boundary of the vehicle driving area.

9. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, It stores computer program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.

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