Mapping method, device, apparatus and storage medium

Abstract

The application provides a mapping method, device, equipment and storage medium. The method comprises the following steps: obtaining a point cloud map of a preset area, wherein the preset area comprises an AGV; generating a two-dimensional grid map based on the point cloud map; determining mapping range coordinates of the AGV when performing autonomous mapping based on the two-dimensional grid map; and sending the mapping range coordinates to the AGV, so that the AGV performs autonomous mapping based on the mapping range coordinates. The AGV can more accurately and quickly find the range, thereby improving the mapping speed of the AGV.

Description

Technical Field

[0001] This application relates to the field of AGV (Automated Guided Vehicle) mapping technology, and particularly to a mapping method, apparatus, device, and storage medium. Background Technology

[0002] As factories worldwide become increasingly automated and factories increasingly utilize robots, AGVs (Automated Guided Vehicles) are a type of factory robot. AGVs can automatically navigate and transport materials, greatly simplifying factory material handling processes and improving material handling efficiency. Currently, AGVs rely on cameras and LiDAR for mapping. However, the lack of bounding points during mapping results in slow mapping efficiency. Summary of the Invention

[0003] To address the aforementioned problems, this application provides a mapping method, apparatus, device, and storage medium that can improve the mapping speed of AGV vehicles.

[0004] This application provides a mapping method, including: Obtain a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; A two-dimensional raster map is generated based on the point cloud map; The coordinates of the mapping range of the AGV vehicle during autonomous mapping are determined based on the two-dimensional grid map. The coordinates of the mapping range are sent to the AGV vehicle so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

[0005] In some embodiments, determining the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map includes: Extract the circumscribed rectangle of the two-dimensional raster map; Determine the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system, wherein the origin of the first pixel coordinate system is the target vertex in the circumscribed rectangle; The first pixel coordinates are converted into third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates, wherein the second pixel coordinate system has the second pixel coordinates as its origin; The mapping range coordinates in the world map are calculated based on the third pixel coordinates to obtain the mapping range coordinates of the AGV during autonomous mapping.

[0006] In some embodiments, converting the first pixel coordinates to third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates includes: Subtracting the second pixel coordinate from the first pixel coordinate of each vertex yields the third pixel coordinate of each first pixel coordinate in the second pixel coordinate system.

[0007] In some embodiments, determining the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system includes: Calculate the first horizontal and vertical coordinate distances between each vertex and the target vertex based on the pixels of each vertex; The second horizontal and vertical coordinate distance between the AGV and the target vertex is calculated based on the pixel of the AGV. Based on the first horizontal and vertical coordinate distances, determine the first pixel coordinates of each vertex in the first pixel coordinate system; Based on the second horizontal and vertical coordinate distance, the second pixel coordinate of the AGV vehicle in the first pixel coordinate system is determined.

[0008] In some embodiments, generating a two-dimensional raster map based on the point cloud map includes: The point cloud map is subjected to pass-through filtering; The point cloud map after pass-through filtering is output to a pre-established raster map processing model to obtain the two-dimensional raster map.

[0009] In some embodiments, sending the mapping range coordinates to the AGV includes: Configure the IP address shared with the AGV vehicle; The coordinates of the mapping range are sent to the AGV based on the IP address.

[0010] In some embodiments, the preset area includes a factory, and the AGV autonomously constructs a map based on the coordinates of the mapping range using a fast expanding random tree algorithm.

[0011] This application provides a mapping method, including: The acquisition module is used to acquire a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; The generation module is used to generate a two-dimensional raster map based on the point cloud map; The determination module is used to determine the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map; The sending module is used to send the coordinates of the mapping range to the AGV vehicle, so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

[0012] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs the mapping method described in any of the above embodiments.

[0013] This application provides a computer-readable storage medium storing a computer program that can be executed by one or more processors and can be used to implement the mapping method described above.

[0014] This application provides a mapping method, apparatus, device, and storage medium. By acquiring a point cloud map of a preset area, wherein the preset area includes an AGV (Automated Guided Vehicle); generating a two-dimensional grid map based on the point cloud map; determining the mapping range coordinates of the AGV during autonomous mapping based on the two-dimensional grid map; and sending the mapping range coordinates to the AGV so that the AGV can autonomously map based on the mapping range coordinates, the AGV can more accurately and quickly find the range, thereby improving the mapping speed of the AGV. Attached Figure Description

[0015] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0016] Figure 1 A schematic diagram illustrating the implementation process of a mapping method provided in this application embodiment; Figure 2 A schematic diagram illustrating the implementation process of a mapping method provided in this application embodiment; Figure 3 A flowchart illustrating the calculation of range coordinates is provided for an embodiment of this application; Figure 4 A flowchart illustrating a coordinate transmission method provided in an embodiment of this application; Figure 5 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application.

[0017] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0020] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] Based on the problems existing in related technologies, this application provides a mapping method. The subject executing the method can be an electronic device, such as a mobile terminal or a computer. The mobile terminal can be a mobile phone or an iPad, and the electronic device can be the controller of the mobile terminal or computer.

[0023] The mapping method provided in this application can achieve its functions by having the processor of an electronic device call program code, wherein the program code can be stored in a computer storage medium.

[0024] This application provides a mapping method. Figure 1 This is a schematic diagram illustrating the implementation process of a mapping method provided in an embodiment of this application, such as... Figure 1 As shown, it includes: Step S101: Obtain a point cloud map of a preset area, wherein the preset area includes an AGV vehicle.

[0025] In this embodiment, the preset area can be a factory area. AGVs can be placed in the factory, and a data acquisition module can be mounted above the factory to capture a point cloud map of the factory. Alternatively, a drone carrying a data acquisition module can be used to capture the point cloud map of the factory. The data acquisition module can be a camera, webcam, etc.

[0026] In this embodiment of the application, the point cloud map can be stored in a PCD file. The point cloud map includes a large number of coordinate points in a preset area.

[0027] In this embodiment of the application, the electronic device can communicate with the acquisition module to obtain a point cloud map of a preset area from the acquisition module.

[0028] In some embodiments, the electronic device can obtain a point cloud map of a preset area from the Internet.

[0029] In some embodiments, an electronic device can input a point cloud map via an input device to obtain a point cloud map of a preset area. The input device can be a storage device, such as a USB flash drive.

[0030] In this embodiment, point cloud information of a preset area can be captured from a top-down perspective. The top-down perspective is achieved when the camera lens is perpendicular to the subject, allowing for the capture of a point cloud image that provides a comprehensive view of the entire area.

[0031] Step S102: Generate a two-dimensional raster map based on the point cloud map.

[0032] In this embodiment of the application, the point cloud data in the point cloud map is three-dimensional, and the Z-axis data of the point cloud data can be compressed to obtain a two-dimensional raster map.

[0033] In this embodiment of the application, step S102 can be implemented through the following steps: Step S1021: Perform pass-through filtering on the point cloud map.

[0034] In this embodiment of the application, during the pass-through filtering process, the desired point cloud can be selected directly according to the conditions set by the filter. It is possible to choose to retain point clouds within a set range or to filter out point clouds within a set range.

[0035] In this embodiment of the application, the desired point cloud can be obtained through pass-through filtering.

[0036] Step S1022: Output the point cloud map after pass-through filtering to the pre-established raster map processing model to obtain the two-dimensional raster map.

[0037] In this embodiment of the application, the raster map processing model is used to manipulate the Z-axis of the point cloud data, compressing the Z-axis downwards to compress it into a two-dimensional raster map.

[0038] Step S103: Determine the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map.

[0039] In this embodiment of the application, the coordinates of the mapping range are determined by the circumscribed rectangle of the preset area.

[0040] In this embodiment of the application, the coordinates of the mapping range are in the world coordinate system.

[0041] In this embodiment of the application, step S103 can be implemented through the following steps: Step S1031: Extract the circumscribed rectangle of the two-dimensional raster map.

[0042] Step S1032: Determine the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system, wherein the origin of the first pixel coordinate system is the target vertex in the circumscribed rectangle.

[0043] In this embodiment of the application, the target point at the upper left corner of the circumscribed rectangle can be determined as the (0,0) point of the first pixel coordinate system.

[0044] In this embodiment, the horizontal and vertical coordinate distances between each vertex, the AGV vehicle, and the origin in the first pixel coordinate system can be calculated based on pixels and resolution, thereby determining the first pixel coordinates of the four vertices of the circumscribed rectangle in the first pixel coordinate system and the second pixel coordinates of the AGV vehicle.

[0045] In this embodiment of the application, step S1032 can be implemented through the following steps: Step S1: Calculate the first horizontal and vertical coordinate distances between each vertex and the target vertex based on the pixels of each vertex.

[0046] In this embodiment of the application, the number of pixels between the X-axis and Y-axis can be determined based on the pixels of each vertex and the pixels of the target vertex. The first horizontal and vertical coordinate distance is obtained by multiplying the number of pixels by the resolution.

[0047] In this embodiment, the number of pixels in the X-axis direction multiplied by the resolution gives the horizontal coordinate distance, and the number of pixels in the Y-axis direction multiplied by the resolution gives the vertical coordinate distance.

[0048] Step S2: Calculate the second horizontal and vertical coordinate distance between the AGV and the target vertex based on the AGV's pixel data.

[0049] In this embodiment of the application, the number of pixels between the X-axis and Y-axis can be determined based on the pixels of the car and the pixels of the target vertex. The second horizontal and vertical coordinate distance is obtained by multiplying the number of pixels by the resolution.

[0050] In this embodiment, the number of pixels in the X-axis direction multiplied by the resolution gives the horizontal coordinate distance, and the number of pixels in the Y-axis direction multiplied by the resolution gives the vertical coordinate distance.

[0051] Step S3: Based on the first horizontal and vertical coordinate distance, determine the first pixel coordinates of each vertex in the first pixel coordinate system.

[0052] In this embodiment of the application, since the target vertex is the origin, after calculating the horizontal and vertical coordinate distances, the first pixel coordinates of each vertex can be determined.

[0053] Step S4: Based on the second horizontal and vertical coordinate distance, determine the second pixel coordinate of the AGV vehicle in the first pixel coordinate system.

[0054] In this embodiment of the application, since the target vertex is the origin, the second pixel coordinate of the AGV vehicle in the first pixel coordinate system is obtained after calculating the second horizontal and vertical coordinate distance.

[0055] Step S1033: Convert the first pixel coordinates into third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates, wherein the second pixel coordinate system has the second pixel coordinates as its origin.

[0056] In this embodiment of the application, since the AGV car uses the car coordinates as the origin when building the map, but now the coordinates of the target vertex are used as the origin, it is necessary to convert the first pixel coordinates.

[0057] In this embodiment, the first pixel coordinates of each vertex can be subtracted from the second pixel coordinates to obtain the third pixel coordinates of each first pixel coordinate in the second pixel coordinate system.

[0058] Step S1034: Calculate the mapping range coordinates in the world map based on the third pixel coordinates to obtain the mapping range coordinates of the AGV vehicle during autonomous mapping.

[0059] In this embodiment of the application, the world coordinates of each vertex can be obtained, and the world coordinates of each vertex are the coordinates of the mapping range.

[0060] Step S104: Send the mapping range coordinates to the AGV vehicle so that the AGV vehicle can autonomously create a map based on the mapping range coordinates.

[0061] In this embodiment of the application, the coordinates of the mapping range can be sent to the AGV vehicle using flash information.

[0062] In this embodiment of the application, after obtaining the coordinates of the mapping range, the AGV can use the fast expanding random tree algorithm to autonomously construct the map.

[0063] In this embodiment, the electronic device and the AGV (Automated Guided Vehicle) can share the same IP address. The path to the file containing the coordinate points to be transmitted is input into the electronic device. The file definition specifies the name and size of the coordinate point file to be transmitted. After these definitions are complete, the file is sent to the designated txt file within the AGV. Upon receiving the coordinate points, the AGV automatically starts autonomous mapping.

[0064] This application provides a mapping method that involves acquiring a point cloud map of a preset area, wherein the preset area includes an AGV (Automated Guided Vehicle); generating a two-dimensional grid map based on the point cloud map; determining the mapping range coordinates of the AGV during autonomous mapping based on the two-dimensional grid map; and sending the mapping range coordinates to the AGV so that the AGV can perform autonomous mapping based on the mapping range coordinates. This method enables the AGV to find the range more accurately and quickly, thereby improving the mapping speed of the AGV.

[0065] Based on the foregoing embodiments, this application provides another mapping method, which uses a point cloud map projected from a top-down view to be converted into a raster map, and uses the raster map to calculate the four coordinate points of the rectangle enclosed by the outermost part of the area; based on the range points given by the top-down view, the coordinates are transmitted to the AGV vehicle using Flask information transmission; the four coordinate points are transmitted to the AGV vehicle, the given range is drawn based on these four points, and the AGV vehicle is started to perform autonomous mapping.

[0066] Figure 2 This is a schematic diagram illustrating the implementation process of a mapping method provided in an embodiment of this application, such as... Figure 2 As shown, it includes: Step S201: Capture point cloud information from a top-down perspective.

[0067] In this embodiment of the application, the point cloud information includes: AGV (Automated Guided Vehicle).

[0068] In this embodiment, the AGV vehicle is placed in a location on the site where it can be captured by a camera, and a camera is set up above the factory to capture point cloud information (same as the point cloud map in the above embodiment).

[0069] Step S202: Project to form a raster map.

[0070] In this embodiment, a pass-through filter is used to organize the point cloud to be processed. The point cloud to be processed is then input into a pre-established raster map processing model. The raster map processing model operates on the z-axis, compressing the z-axis downwards little by little, gradually compressing it into a two-dimensional graphic, thus forming a two-dimensional raster map.

[0071] Step S203: Calculate the coordinates of the area to be mapped independently under the raster map (same as the mapping area coordinates in the above embodiment).

[0072] Figure 3 This application provides a flowchart illustrating the calculation of range coordinates in an embodiment of the present application. Figure 3 As shown, it includes: Step S2031: Process the raster map.

[0073] Step S2032: Extract the circumscribed rectangle.

[0074] In this embodiment of the application, when extracting the circumscribed rectangle, the car pixels are also extracted.

[0075] Step S2033: Find the vertex pixel coordinates.

[0076] In this embodiment, the four vertices of the external rectangle to be constructed and the pixel coordinates of the car can be selected with the top left corner of the image as (0, 0).

[0077] Step S2034: Convert to pixel coordinates with the car as the origin.

[0078] In this embodiment of the application, since the AGV car builds the map autonomously with the car coordinates as the origin, but now the coordinates of the upper left corner of the image are used as the origin, the car coordinates are subtracted from the four vertices of the calculated circumscribed rectangle to obtain the pixel coordinates of the four vertices with the car as the origin.

[0079] Step S2035: Convert pixel coordinates to world coordinates.

[0080] Step S204: Transfer the coordinates to the AGV.

[0081] In this embodiment of the application, the calculated coordinates are transmitted via Flask.

[0082] Figure 4 This is a flowchart illustrating a coordinate transmission method provided in an embodiment of this application, as shown below. Figure 4 As shown, it includes: Step S2041: Connect the AGV and the computer to the same IP address.

[0083] Step S2042: Provide the file path to be transferred.

[0084] Step S2043: Define file information.

[0085] Step S2044: Send file information.

[0086] Step S2045: Send the transferred file to the TXT document.

[0087] In step S205, the AGV receives the coordinates to divide the designated area.

[0088] Step S206: Enable the RRT algorithm (see figure).

[0089] The method provided in this application enables AGVs to quickly and accurately define the mapping area, and to more quickly create the desired grid map size in the factory, thereby improving the mapping speed of AGVs. This is of great significance for more accurately and quickly finding the area and creating large maps.

[0090] Based on the foregoing embodiments, this application provides a mapping device. The modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0091] This application provides a mapping apparatus, including: The acquisition module is used to acquire a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; The generation module is used to generate a two-dimensional raster map based on the point cloud map; The determination module is used to determine the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map; The sending module is used to send the coordinates of the mapping range to the AGV vehicle, so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

[0092] In some embodiments, determining the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map includes: Extract the circumscribed rectangle of the two-dimensional raster map; Determine the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system, wherein the origin of the first pixel coordinate system is the target vertex in the circumscribed rectangle; The first pixel coordinates are converted into third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates, wherein the second pixel coordinate system has the second pixel coordinates as its origin; The mapping range coordinates in the world map are calculated based on the third pixel coordinates to obtain the mapping range coordinates of the AGV during autonomous mapping.

[0093] In some embodiments, converting the first pixel coordinates to third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates includes: Subtracting the second pixel coordinate from the first pixel coordinate of each vertex yields the third pixel coordinate of each first pixel coordinate in the second pixel coordinate system.

[0094] In some embodiments, determining the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system includes: Calculate the first horizontal and vertical coordinate distances between each vertex and the target vertex based on the pixels of each vertex; The second horizontal and vertical coordinate distance between the AGV and the target vertex is calculated based on the pixel of the AGV. Based on the first horizontal and vertical coordinate distances, determine the first pixel coordinates of each vertex in the first pixel coordinate system; Based on the second horizontal and vertical coordinate distance, the second pixel coordinate of the AGV vehicle in the first pixel coordinate system is determined.

[0095] In some embodiments, generating a two-dimensional raster map based on the point cloud map includes: The point cloud map is subjected to pass-through filtering; The point cloud map after pass-through filtering is output to a pre-established raster map processing model to obtain the two-dimensional raster map.

[0096] In some embodiments, sending the mapping range coordinates to the AGV includes: Configure the IP address shared with the AGV vehicle; The coordinates of the mapping range are sent to the AGV based on the IP address.

[0097] In some embodiments, the preset area includes a factory, and the AGV autonomously constructs a map based on the coordinates of the mapping range using a fast expanding random tree algorithm.

[0098] It should be noted that, in the embodiments of this application, if the above-described mapping method 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. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0099] Accordingly, embodiments of this application provide a computer-readable storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps in the mapping method provided in the above embodiments.

[0100] This application provides an electronic device; Figure 5 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application, such as... Figure 5 As shown, the electronic device 500 includes: a processor 501, at least one communication bus 502, a user interface 503, at least one external communication interface 504, and a memory 505. The communication bus 502 is configured to enable communication between these components. The user interface 503 may include a control panel, and the external communication interface 504 may include standard wired and wireless interfaces. The processor 501 is configured to execute a program of a mapping method stored in the memory to implement the steps of the mapping method provided in the above embodiment.

[0101] This application provides a mapping method, including: Obtain a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; A two-dimensional raster map is generated based on the point cloud map; The coordinates of the mapping range of the AGV vehicle during autonomous mapping are determined based on the two-dimensional grid map. The coordinates of the mapping range are sent to the AGV vehicle so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

[0102] In some embodiments, determining the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map includes: Extract the circumscribed rectangle of the two-dimensional raster map; Determine the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system, wherein the origin of the first pixel coordinate system is the target vertex in the circumscribed rectangle; The first pixel coordinates are converted into third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates, wherein the second pixel coordinate system has the second pixel coordinates as its origin; The mapping range coordinates in the world map are calculated based on the third pixel coordinates to obtain the mapping range coordinates of the AGV during autonomous mapping.

[0103] In some embodiments, converting the first pixel coordinates to third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates includes: Subtracting the second pixel coordinate from the first pixel coordinate of each vertex yields the third pixel coordinate of each first pixel coordinate in the second pixel coordinate system.

[0104] In some embodiments, determining the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system includes: Calculate the first horizontal and vertical coordinate distances between each vertex and the target vertex based on the pixels of each vertex; The second horizontal and vertical coordinate distance between the AGV and the target vertex is calculated based on the pixel of the AGV. Based on the first horizontal and vertical coordinate distances, determine the first pixel coordinates of each vertex in the first pixel coordinate system; Based on the second horizontal and vertical coordinate distance, the second pixel coordinate of the AGV vehicle in the first pixel coordinate system is determined.

[0105] In some embodiments, generating a two-dimensional raster map based on the point cloud map includes: The point cloud map is subjected to pass-through filtering; The point cloud map after pass-through filtering is output to a pre-established raster map processing model to obtain the two-dimensional raster map.

[0106] In some embodiments, sending the mapping range coordinates to the AGV includes: Configure the IP address shared with the AGV vehicle; The coordinates of the mapping range are sent to the AGV based on the IP address.

[0107] In some embodiments, the preset area includes a factory, and the AGV autonomously constructs a map based on the coordinates of the mapping range using a fast expanding random tree algorithm.

[0108] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0109] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0110] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and 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. In addition, the coupling, direct coupling, or communication connection between the controlled or discussed components can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0112] The units described above as separate components may or may not be physically separate. The components controlled by the units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0113] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0114] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0115] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0116] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A mapping method, characterized in that, include: Obtain a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; A two-dimensional raster map is generated based on the point cloud map; Determining the mapping range coordinates of the AGV during autonomous mapping based on the two-dimensional grid map includes: extracting the circumscribed rectangle of the two-dimensional grid map; determining the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in a first pixel coordinate system, wherein the origin of the first pixel coordinate system is the target vertex in the circumscribed rectangle; converting the first pixel coordinates into third pixel coordinates in a second pixel coordinate system based on the second pixel coordinates, wherein the second pixel coordinate system has the second pixel coordinates as its origin; and calculating the mapping range coordinates in the world map based on the third pixel coordinates to obtain the mapping range coordinates of the AGV during autonomous mapping. The coordinates of the mapping range are sent to the AGV vehicle so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

2. The method according to claim 1, characterized in that, The step of converting the first pixel coordinates to third pixel coordinates in the second pixel coordinate system based on the second pixel coordinates includes: Subtracting the second pixel coordinate from the first pixel coordinate of each vertex yields the third pixel coordinate of each first pixel coordinate in the second pixel coordinate system.

3. The method according to claim 1, characterized in that, Determining the first pixel coordinates of the four vertices of the circumscribed rectangle and the second pixel coordinates of the AGV in the first pixel coordinate system includes: Calculate the first horizontal and vertical coordinate distances between each vertex and the target vertex based on the pixels of each vertex; The second horizontal and vertical coordinate distance between the AGV and the target vertex is calculated based on the pixel of the AGV. Based on the first horizontal and vertical coordinate distances, determine the first pixel coordinates of each vertex in the first pixel coordinate system; Based on the second horizontal and vertical coordinate distance, the second pixel coordinate of the AGV vehicle in the first pixel coordinate system is determined.

4. The method according to claim 1, characterized in that, The generation of a two-dimensional raster map based on the point cloud map includes: The point cloud map is subjected to pass-through filtering; The point cloud map after pass-through filtering is output to a pre-established raster map processing model to obtain the two-dimensional raster map.

5. The method according to claim 1, characterized in that, Sending the coordinates of the mapped area to the AGV includes: Configure the IP address shared with the AGV vehicle; The coordinates of the mapping range are sent to the AGV based on the IP address.

6. The method according to any one of claims 1-5, characterized in that, The preset area includes a factory, and the AGV (Automated Guided Vehicle) autonomously constructs a map based on the coordinates of the mapping range using a fast expanding random tree algorithm.

7. A mapping apparatus applying the method of claim 1, characterized in that, include: The acquisition module is used to acquire a point cloud map of a preset area, wherein the preset area includes: AGV vehicles; The generation module is used to generate a two-dimensional raster map based on the point cloud map; The determination module is used to determine the mapping range coordinates of the AGV vehicle during autonomous mapping based on the two-dimensional grid map; The sending module is used to send the coordinates of the mapping range to the AGV vehicle, so that the AGV vehicle can autonomously create a map based on the coordinates of the mapping range.

8. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the mapping method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the mapping method as described in any one of claims 1 to 6.

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