Automatic mapping method and device

Abstract

This application provides an automatic mapping method and apparatus, comprising: generating an initial boundary map in response to multiple initial boundary coordinates selected by a user in a remote sensing image; controlling a self-moving device to travel along the initial boundary and obtain target travel data based on the initial boundary map; and updating the initial boundary map based on the target travel data to obtain a target boundary map. This application implements automatic mapping through preliminary remote sensing map construction and optimized mapping using a self-moving device, which is beneficial for improving the accuracy and flexibility of automatic mapping.

Description

Technical Field

[0001] The present application relates to the field of map construction technology, and in particular to an automatic map construction method and device. Background Art

[0002] There are two common mapping solutions. One is that users control the autonomous vehicle along the area boundary and generate a closed area based on the vehicle's driving path. The other is that some autonomous vehicles are equipped with radar and use the radar to scan surrounding objects to generate a closed area.

[0003] Existing manually controlled mapping solutions for mobile devices require users to repeatedly adjust the path to ensure boundary integrity. This is especially cumbersome and error-prone for large or irregular areas. Furthermore, areas cannot be quickly modified or segmented, and repeated operations are required to divide multiple sub-areas. Furthermore, existing radar scanning solutions are highly dependent on the environment. Complex areas, such as depressions, water bodies, or complex obstacles, may result in missed detections or misjudgments. Furthermore, it is difficult to define differentiated boundaries for multiple sub-areas within the same area, making it impossible to meet users' needs for fast, accurate, and flexible mapping of target areas. Summary of the Invention

[0004] This application provides an automatic mapping method and device, which aims to automatically and accurately complete map creation through preliminary mapping of remote sensing maps and optimized mapping by running on a mobile device. There is no need for the user to control the device to draw the map, which reduces the user's time and learning cost. At the same time, it can personalize the creation of multiple areas in a complete area, thereby improving the accuracy and flexibility of automatic mapping.

[0005] In a first aspect, the present application provides an automatic mapping method, the method comprising:

[0006] generating an initial boundary map in response to a plurality of initial boundary coordinates selected by a user in the remote sensing image;

[0007] Controlling the mobile device to travel along the initial boundary based on the initial boundary map and acquiring target travel data;

[0008] The initial boundary map is updated according to the target driving data to obtain a target boundary map.

[0009] In a second aspect, an embodiment of the present application provides an automatic mapping device, the device comprising:

[0010] a response unit for generating an initial boundary map in response to a plurality of initial boundary coordinates selected by a user in the remote sensing map;

[0011] An acquisition unit, configured to control the mobile device to travel along the initial boundary based on the initial boundary map and to acquire target travel data;

[0012] A processing unit is configured to update the initial boundary map according to the target driving data to obtain a target boundary map.

[0013] In a third aspect, an embodiment of the present application provides a self-mobile device comprising a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the first aspect of the embodiment of the present application.

[0014] In a fourth aspect, an embodiment of the present application provides a terminal device comprising a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program comprises instructions for executing the steps in the first aspect of the embodiment of the present application.

[0015] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program / instruction is stored, and the computer program / instruction is executed by a processor to implement the steps of the method described in the first aspect above.

[0016] In a sixth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application.

[0017] As can be seen, in the embodiment of the present application, an initial boundary map is first generated in response to multiple initial boundary coordinates selected by the user in the remote sensing image; based on the initial boundary map, the self-mobile device is controlled to travel along the initial boundary and obtain target travel data; and the initial boundary map is updated according to the target travel data to obtain the target boundary map. In this way, the present application realizes automatic mapping by controlling the self-mobile device to travel along the initial boundary and obtain target travel data to update the map, optimizes the boundary according to the device travel data, improves the automation, accuracy, flexibility and safety of mapping, reduces user operation and learning costs, and meets personalized needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1This is a schematic diagram of the system architecture of an automatic mapping system provided in an embodiment of the present application;

[0020] Figure 2 This is a schematic structural diagram of a self-moving device provided in an embodiment of the present application;

[0021] Figure 3 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present application;

[0022] Figure 4 This is a flow chart of an automatic mapping method provided in an embodiment of the present application;

[0023] Figure 5 This is a schematic diagram of an interface for constructing an initial boundary map provided in an embodiment of the present application;

[0024] Figure 6 This is a schematic diagram of a boundary expansion scenario provided by an embodiment of the present application;

[0025] Figure 7 This is a schematic diagram of a display interface of a target boundary map provided in an embodiment of the present application;

[0026] Figure 8 This is a block diagram of the functional units of an automatic mapping device provided in an embodiment of the present application;

[0027] Figure 9 This is a block diagram of the functional units of another automatic mapping device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0029] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0030] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] In the embodiments of this application, "and / or" describes the relationship between associated objects and indicates that three relationships can exist. For example, "A and / or B" can represent the following three situations: A exists alone; A and B exist simultaneously; and B exists alone. A and B can be singular or plural.

[0032] In the embodiments of the present application, the symbol " / " can indicate that the preceding and following objects are in an "or" relationship. In addition, the symbol " / " can also represent a division sign, that is, performing a division operation. For example, A / B can mean A divided by B.

[0033] In the embodiments of the present application, "at least one item" or similar expressions refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more. For example, at least one item (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0034] In the embodiments of this application, "equal to" can be used in conjunction with "greater than" and is applicable to the technical solution adopted when "greater than" is used, and can also be used in conjunction with "less than" and is applicable to the technical solution adopted when "less than" is used. When "equal to" is used in conjunction with "greater than", it should not be used in conjunction with "less than"; when "equal to" is used in conjunction with "less than", it should not be used in conjunction with "greater than".

[0035] Existing manually controlled mapping solutions for mobile devices require users to repeatedly adjust the path to ensure boundary integrity. This is especially cumbersome and error-prone for large or irregular areas. Furthermore, areas cannot be quickly modified or segmented, and repeated operations are required to divide multiple sub-areas. Furthermore, existing radar scanning solutions are highly dependent on the environment. Complex areas, such as depressions, water bodies, or complex obstacles, may result in missed detections or misjudgments. Furthermore, it is difficult to define differentiated boundaries for multiple sub-areas within the same area, making it impossible to meet users' needs for fast, accurate, and flexible mapping of target areas.

[0036] In response to the above problems, an embodiment of the present application provides an automatic mapping method and device, which is described in detail below with reference to the accompanying drawings.

[0037] See also Figure 1 , Figure 1 This is a schematic diagram of the system architecture of an automatic mapping system provided in an embodiment of the present application. Figure 1 As shown, the automatic mapping system includes a mobile device 110 and a terminal device 120, and the mobile device 110 is communicatively connected to the terminal device 120; specifically, the mobile device 110 and the terminal device 120 may include interactive modules such as an electronic screen, and the user can view relevant information through the electronic screen and realize human-computer interaction operations by touching the electronic screen.

[0038] Among them, the self-mobile device 110 is the entity that performs mapping operations, such as a lawn mower. The core functions of the self-mobile device 110 include data acquisition, relying on multimodal perception such as GPS, IMU, vision / radar sensors, etc. to obtain location and environmental data while driving, providing a basis for boundary drawing and map optimization; and execution control, that is, receiving instructions from the terminal device 120, driving along the planned boundary, and completing the "initial boundary verification-dynamic data acquisition-map correction" closed loop; and including safety interaction, specifically with obstacle avoidance and dangerous scene processing capabilities, such as "cliff detection, collision detection", etc., to ensure the stability and safety of the mapping process. In addition, the self-mobile device 110 can also load satellite / remote sensing images through the interactive module, support users to select initial boundary coordinates, complete "coordinate simplification, conversion, and legality verification", and generate a theoretical mapping path.

[0039] Among them, the terminal device 120 is the core entrance for user operation and data processing. The core functions of the terminal device 120 include interaction and planning, specifically loading satellite / remote sensing images, supporting users to select initial boundary coordinates, completing "coordinate simplification, conversion, and legality verification", and generating theoretical mapping paths; and including data collaboration, that is, receiving driving data sent back from mobile devices, such as actual trajectories, environmental perception information, etc., comparing and optimizing theoretical boundaries to achieve "dynamic map correction"; and including result output, specifically integrating mapping data, generating recording reports, supporting users to confirm and modify maps, and finally outputting executable work areas.

[0040] The following describes in detail the system architecture involved in the embodiments of the present application.

[0041] The present application also provides a self-mobile device 20, such as Figure 2 As shown, Figure 2: is a structural diagram of a self-moving device provided in an embodiment of the present application. The self-moving device 20 includes at least one processor 21, a display screen 22, and a memory 23. It may also include a communications interface 25 and a bus 24. The processor 21, the display screen 22, the memory 23, and the communications interface 25 can communicate with each other through the bus 24. The display screen 22 is configured to display a preset user guidance interface in the initial setting mode. The communications interface 25 can transmit information. One or more programs are stored on the memory 23 and are configured to be executed by the processor 21. The one or more programs include instructions for executing any step in the following method embodiments. In a specific implementation, the processor 21 can call the logic instructions in the memory 23 to execute any step in the following method embodiments, and when performing data transmission such as sending, the communications interface 25 can be selectively called to complete the corresponding operation.

[0042] This application also provides a terminal device 30, such as Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present application. The terminal device 30 may include one or more of the following components: a memory, a processor, a communication bus, a communication interface, and one or more programs. The one or more programs are stored in the memory and configured to be executed by the processor. The one or more programs include instructions for executing any step in the following method embodiments. In a specific implementation, the processor is used to execute any step in the following method embodiments, and when performing data transmission such as sending, it may optionally call the communication interface to complete the corresponding operation.

[0043] The following combination Figure 4 An automatic mapping method provided in an embodiment of the present application is described. Figure 4 This is a flow chart of an automatic mapping method provided in an embodiment of the present application. The automatic mapping method is applied to Figure 1 The self-mobile device 110 or terminal device 120 in the automatic mapping system shown specifically includes the following steps:

[0044] Step 410 : generating an initial boundary map in response to a plurality of initial boundary coordinates selected by a user in the remote sensing image.

[0045] Among them, remote sensing images are image data obtained by using remote sensing technology, using sensors carried by aircraft, satellites, drones and other platforms to detect information on the earth's surface or atmosphere and convert it into image data. They can present information such as electromagnetic waves reflected or radiated by ground objects. Common types include: (1) by sensor / band: specifically including visible light remote sensing images, panchromatic remote sensing images, multispectral remote sensing images, hyperspectral remote sensing images, and infrared remote sensing images; (2) by imaging method: specifically including laser radar (LiDAR) images, synthetic aperture radar remote sensing images, and images obtained by aerial photography imaging (such as drone aerial images).

[0046] In one possible embodiment, in response to a plurality of initial boundary coordinates selected by a user in a remote sensing image, an initial boundary map is generated, including: in response to the user's selection operation for the plurality of initial boundary coordinates in the remote sensing image, performing a first preset operation on the plurality of initial boundary coordinates to obtain a plurality of first boundary coordinates; performing a legitimacy judgment on the plurality of first boundary coordinates based on a preset coordinate type to obtain a target judgment result, the coordinate type including a lawn type and a non-lawn type; performing a second preset operation based on the target judgment result to obtain a plurality of second boundary coordinates; and generating the initial boundary map based on the plurality of second boundary coordinates.

[0047] Among them, the selection operation is the interactive action performed by the user on the remote sensing image interface to define the initial boundary of the map. The operation forms include manual selection, such as marking boundary points one by one on the remote sensing image by clicking the mouse or touching the screen with the finger; and continuous drawing, such as dragging the mouse or sliding the touch screen to draw continuous line segments on the image, and the system automatically extracts the line segment vertices as boundary coordinates; and includes auxiliary tool point selection, such as using tools such as "rectangular selection, polygon fitting", etc., after selecting the area, the system automatically identifies the boundary vertices to simplify the user's point-by-point marking process.

[0048] Specifically, see Figure 5 , Figure 5 This is a schematic diagram of an initial boundary map construction interface provided by an embodiment of the present application, such as Figure 5 As shown, in the manual mapping interface, the user manually selects initial boundary coordinates 51 to construct the initial boundary.

[0049] Figure 5In the manual mapping interface, a remote sensing image is displayed in the middle, with the image centered on the mobile device 52 (e.g., a lawn mower). The latitude and longitude (114°12′16″ E, 33°46′23″ N), map level (14), and scale (500 meters) are marked below the image to provide a geographic reference for the user to select a point. On the left is a function navigation bar, with “Manual Mapping” currently selected for entering the manual mapping process. In addition, there are multiple function navigation bars such as “User Center,” “Target Map,” “Vehicle Management,” and “Terminal Management.” On the right is a map operation area with tools such as layer visibility, 2D and 3D switching, measurement, and vehicle positioning to assist the user in mapping operations.

[0050] It can be seen that in this embodiment, the user can manually select multiple initial boundary coordinates in the remote sensing image interface to form an initial boundary, and then optimize the initial boundary based on the driving data by controlling the mobile device to obtain a more accurate target boundary map.

[0051] In one possible embodiment, the first preset operation includes a coordinate simplification operation and a coordinate conversion operation; performing the first preset operation on the multiple initial boundary coordinates to obtain multiple first boundary coordinates includes: performing the coordinate simplification operation on the multiple initial boundary coordinates according to a preset coordinate simplification algorithm to simplify the continuous dense coordinates to obtain multiple reference boundary coordinates, where the reference boundary coordinates are pixel coordinates; performing the coordinate conversion operation according to a preset coordinate conversion algorithm to convert the multiple reference boundary coordinates into the multiple first boundary coordinates, where the first boundary coordinates are latitude and longitude coordinates.

[0052] Coordinate simplification algorithms are used to process dense, redundant coordinates generated by continuous drawing and frequent clicks when users select points, preserving key contours and eliminating invalid points. Coordinate simplification algorithms can be either the Douglas-Peucker algorithm, which sets a "distance threshold" and traverses the coordinate sequence, recursively removing points whose distance from the fitted line segment is less than the threshold, while retaining key coordinates such as inflection points and vertices. Alternatively, the perpendicular distance method calculates the perpendicular distance between adjacent points and the line connecting the preceding and succeeding points, removing points with excessively small distances, and still restoring the boundary shape after simplification.

[0053] Coordinate conversion algorithms are used to convert pixel coordinates (e.g., screen coordinates (x, y)) on remote sensing images into geographic coordinates (e.g., WGS84, GCJ02) for easy recognition and execution on mobile devices. Coordinate conversion can rely on the geo-reference of remote sensing images, where the images contain inherent "pixel coordinate ↔ geographic coordinate" conversion parameters (e.g., affine transformation matrix, projection parameters). Alternatively, coordinate conversion can be implemented using algorithms that convert pixel points (x, y) to latitude and longitude (lon, lat) using spatial transformation models and the image metadata, including the "upper left corner geographic coordinates, resolution, and rotation parameters."

[0054] It is understandable that coordinate simplification transforms the user's rough operation of "drawing boundaries at will" into streamlined data that "the system can efficiently process"; coordinate conversion converts "image virtual coordinates" into "device-executable geographic coordinates", performs fine processing on the coordinates, and improves mapping efficiency and accuracy.

[0055] In a possible embodiment, the actual geographical scene corresponding to the lawn type representation coordinates is lawn, and the actual geographical scene corresponding to the non-lawn type representation coordinates is non-lawn; the legitimacy judgment of the multiple first boundary coordinates based on the preset coordinate type is obtained to obtain a target judgment result, including: for each first boundary coordinate in the multiple first boundary coordinates, judging the coordinate type of the first boundary coordinate; if the coordinate type is a lawn type, the first judgment result is that the first boundary coordinate is a legal boundary coordinate; if the coordinate type is a non-lawn type, the second judgment result is that the first boundary coordinate is an illegal boundary coordinate.

[0056] It is understandable that if the mobile device is a lawn mower, it is necessary to consider the boundary coordinates of the mapping area as lawn when automatically building the map, filter out non-lawn coordinates (for example, if the user mistakenly selects a road or flower bed), and avoid the lawn mower driving in non-operating areas, thereby reducing ineffective work and equipment loss.

[0057] Among them, the method for judging the legitimacy of the coordinate type may include judging the coordinate type through the queryRenderFeatures interface provided by the Mapbox platform; judging based on the rules of the spectral characteristics of the remote sensing image, specifically using the multispectral data of the remote sensing image, and realizing the judgment through the vegetation index threshold or color space filtering; based on the field verification of the multimodal perception system, specifically combining the visual sensor (such as camera) or radar carried by the mobile device, to perform real-time perception verification of the coordinate corresponding area during driving. This application does not limit the specific method of judging the legitimacy of the coordinates.

[0058] It should be clarified that whether to distinguish between lawn coordinates and non-lawn coordinates, and whether to judge the validity of coordinates based on the coordinate type, needs to be specifically selected according to the specific application scenario and the device type of the self-moving device. It is also possible not to judge and filter the coordinate type.

[0059] In a possible embodiment, the second preset operation is performed according to the target judgment result to obtain multiple second boundary coordinates, including: judging that the coordinates currently selected by the user are illegal boundary coordinates according to the second judgment result; performing the second preset operation to prompt the user to reselect boundary coordinates through a pop-up window; judging that the boundary coordinates reselected by the user are legal boundary coordinates; and determining all legal boundary coordinates selected by the user as the second boundary coordinates.

[0060] It is understandable that when the user selects coordinates for the first time, the legality of each selected single coordinate is judged. If the coordinate is legal, it is retained. If it is illegal, a pop-up window prompts the user to reselect the coordinate. Finally, multiple legal coordinates selected by the user are obtained. This ensures that the operating boundary of the self-moving device is within the real legal area, ensures the effectiveness of mapping and the accuracy of equipment operation, and improves mapping quality and operation safety.

[0061] In a possible embodiment, the method further includes: determining the total number and point distribution status of the multiple second boundary coordinates; when it is detected that the total number of the multiple second boundary coordinates is less than a preset number threshold, and / or the point distribution status of the multiple second boundary coordinates is a collinear state, executing a third preset operation to prompt the user to continue to supplement the selected boundary coordinates through a pop-up window.

[0062] For example, if the total number of multiple legal second boundary coordinates finally determined is less than 3, or are in a collinear state, the polygonal area boundary cannot be formed. Therefore, the user needs to be prompted to continue selecting coordinates and repeat the above-mentioned "first preset operation", "legality judgment", and "second preset operation" for the latest selected coordinates, so as to obtain a total number greater than 3 and multiple second boundary coordinates that are not in a collinear state to generate the initial boundary.

[0063] It can be seen that in this embodiment, the user selects the initial boundary coordinates on the remote sensing image, and after coordinate simplification, coordinate conversion and legality judgment, the user is prompted to correct or supplement the coordinates, and an initial boundary map consisting of legal and valid coordinates is generated, realizing the combination of low-threshold interaction and intelligent processing, thereby improving mapping efficiency and accuracy.

[0064] Step 420 : Control the mobile device to travel along the initial boundary based on the initial boundary map and obtain target travel data.

[0065] The user may create an initial boundary map on a mobile device or terminal device, and after obtaining the initial boundary map from the mobile device, start driving based on the initial boundary in the initial boundary map.

[0066] In a possible embodiment, the initial boundary includes multiple third boundary coordinates, and the multiple third boundary coordinates are obtained by performing a fourth preset operation on the multiple second boundary coordinates; controlling the self-moving device to travel along the initial boundary and obtaining target driving data based on the initial boundary map includes: controlling the self-moving device to travel along the initial boundary and obtaining operating data during the driving process; controlling the self-moving device to spin and scan the surrounding environment when traveling to the third boundary coordinates to obtain environmental data; and determining the target driving data based on the operating data and the environmental data.

[0067] Among them, operation data includes the device's own operating status data such as position coordinates, driving speed, driving direction, mileage, etc. during the mobile device's driving along the initial boundary; environmental data includes but is not limited to environmental perception data such as obstacle location, terrain undulations, vegetation distribution, and dangerous areas (such as cliffs and water areas).

[0068] In a possible embodiment, the multiple third boundary coordinates are obtained by performing a fourth preset operation on the multiple second boundary coordinates, including: performing preprocessing on the multiple second boundary coordinates, the preprocessing including deduplication processing and interpolation processing; generating an optimal triangular mesh based on the Delaunay triangulation algorithm and the multiple second boundary coordinates that have undergone the preprocessing, the optimal triangular mesh covering the multiple second boundary coordinates that have undergone the preprocessing; generating an original boundary area based on the α-shape algorithm and the optimal triangular mesh; performing Minkowski shrinkage on the original boundary area according to the GPS positioning error radius to obtain the initial boundary; determining the multiple third boundary coordinates located on the initial boundary, the multiple third boundary coordinates corresponding one-to-one to the multiple second boundary coordinates.

[0069] It can be understood that the "first preset operation", "legality judgment" and "second preset operation" are performed in sequence for the initial coordinates selected by the user to obtain multiple second boundary coordinates, and then deduplication and difference processing are performed on the multiple second boundary coordinates, and the initial boundary is finally determined based on multiple algorithms and boundary shrinkage. In this way, the third boundary coordinate located on the initial boundary is offset from the second boundary coordinate position, but the quantity is corresponding.

[0070] In a possible embodiment, controlling the self-moving device to travel along the initial boundary includes: determining a third boundary coordinate among the multiple third boundary coordinates that is closest to the initial coordinate of the self-moving device; and controlling the self-moving device to travel along the initial boundary starting from the third boundary coordinate that is closest to the initial coordinate until traversing the multiple third boundary coordinates.

[0071] It can be seen that in this embodiment, the "nearest point first + ordered traversal" strategy solves the path planning problem when building maps on mobile devices, and achieves an efficient conversion from "user-defined boundaries" to "device physical execution", which is conducive to reducing manual intervention, improving mapping efficiency, and ensuring the orderliness of data collection.

[0072] In one possible embodiment, the self-moving device is configured with a multimodal perception system, which is used to control the self-moving device to execute a dangerous scene processing strategy and an obstacle avoidance strategy during driving; the dangerous scene processing strategy includes a first processing strategy and a second processing strategy, which is used to control the self-moving device to execute a corresponding control strategy when it identifies dangerous scenes with different danger levels in the front area; the obstacle avoidance strategy includes a static obstacle avoidance strategy, a low-speed obstacle avoidance strategy and a high-speed obstacle avoidance strategy, which is used to control the self-moving device to execute a corresponding control strategy based on the movement state of the obstacle when it identifies the existence of an obstacle in the front area.

[0073] The multimodal perception system includes but is not limited to binocular stereo vision: an RGB camera with a baseline spacing of 20 cm, capturing images at 30 fps, and generating a depth map in real time (effective range of 0.3-5 meters); a thermal imager: detecting sudden changes in surface temperature (triggering an early warning when the temperature difference in the pool area is >3°C); a millimeter-wave radar: scanning the 120° area in front in the 77GHz frequency band to detect the relative speed of dynamic objects; and an inertial measurement unit (IMU): monitoring the tilt angle of the vehicle body (a pitch angle >25° is judged as a cliff risk).

[0074] Specifically, the binocular stereo vision scanning strategy includes a front-view main scanning area centered on the front of the vehicle, a horizontal scanning angle of ±60°, and a vertical viewing angle of -15° to +10° (focusing on detecting sudden changes in the ground); side auxiliary scanning, using a fisheye lens to cover a 1-meter range on both sides of the vehicle body to prevent scratches during turning.

[0075] Furthermore, the multimodal perception system adopts a layered detection mechanism. Specifically, in the near-field warning zone (0-1.5 meters), the highest detection frequency (100ms / time) is used; in the mid-field observation zone (1.5-3 meters), the normal detection frequency (300ms / time) is used; and in the far-field warning zone (3-5 meters), the feature extraction mode is used to save computing power.

[0076] In one possible embodiment, the danger level of the dangerous scene corresponding to the first processing strategy is higher than the danger level of the dangerous scene corresponding to the second processing strategy; the first processing strategy is to control the self-moving device to stop driving and generate a first alarm message to prompt the user to implement rescue; the second processing strategy is to control the self-moving device to slow down to the target speed, perform a visual scan for a preset time, start a high-frequency sampling mode, and generate a second alarm message.

[0077] Among them, the dangerous scenes corresponding to the first processing strategy include high-risk scenes including pool scenes, deep pit scenes and cliff scenes.

[0078] In one possible embodiment, the static obstacle avoidance strategy is to record the obstacle coordinates and plan a detour route based on the obstacle coordinates, and then control the self-moving device to continue driving according to the detour route; the low-speed obstacle avoidance strategy is to control the self-moving device to issue an audible and visual warning within a preset time period, and at the same time control the self-moving device to drive at a low speed or stop; the high-speed obstacle avoidance strategy is to control the self-moving device to emergency brake and reverse for a preset distance and then stop when it is detected that the expected moving trajectory of the high-speed obstacle intersects with the expected driving trajectory of the self-moving device, and generate a third alarm message to prompt the user to implement rescue.

[0079] For example, if a static obstacle does not move within 5 seconds, the obstacle coordinates are recorded and a detour route is planned; if a low-speed obstacle has a speed of less than 0.2m / s, an audible and visual warning is issued, and the vehicle slows down or waits for 10 minutes; if a high-speed obstacle has a speed greater than 1m / s and the trajectories intersect, emergency braking is performed and the vehicle reverses 0.5m, and an alarm message is generated to prompt the user to come for rescue.

[0080] It can be seen that in this embodiment, by controlling the mobile device to travel along the initial boundary according to the "nearest point first + ordered traversal" strategy, combined with the multimodal perception system to collect operation and environmental data, to perform hazard classification processing and multi-strategy obstacle avoidance, efficient mapping, accurate environmental perception and safe operation are achieved.

[0081] Step 430 : Update the initial boundary map according to the target driving data to obtain a target boundary map.

[0082] In one possible embodiment, the initial boundary map is updated according to the target driving data to obtain the target boundary map, including: when it is detected that the self-moving device travels to the third boundary coordinate, performing a boundary expansion operation according to the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate; when it is detected that the self-moving device has traversed the multiple third boundary coordinates, obtaining multiple expanded boundary coordinates; and generating the target boundary map according to the multiple expanded boundary coordinates.

[0083] It is understandable that the mobile device does not necessarily perform the border expansion operation at every third border coordinate, and after traversing multiple third border coordinates, it may only obtain one or more expanded border coordinates.

[0084] In a possible embodiment, the boundary expansion operation is performed based on the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate, including: determining the boundary outside area corresponding to the third boundary coordinate on the initial boundary; making a safety judgment on the boundary outside area based on the operating data and the environmental data of the self-moving device at the third boundary coordinate; if the boundary outside area is a safe area, controlling the self-moving device to move outward from the third boundary coordinate to the boundary outside area and to the expanded boundary coordinate based on a preset boundary optimization algorithm to achieve boundary expansion.

[0085] Among them, this application does not limit the specific algorithm scheme for determining the area outside the boundary and making security judgments on the area outside the boundary. The security judgments on the area outside the boundary are made to determine whether the mobile device can safely expand outward so as to appropriately adjust the initial boundary.

[0086] In a possible embodiment, after performing a boundary expansion operation based on the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate, the method further includes: controlling the self-moving device to continue moving from the expanded boundary coordinate to the next third boundary coordinate located on the initial boundary; when it is detected that the self-moving device has moved to the next third boundary coordinate, repeating the above-mentioned step of performing a boundary expansion operation based on the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the next third boundary coordinate.

[0087] Specifically, see Figure 6 , Figure 6 This is a schematic diagram of a boundary expansion scenario provided by an embodiment of the present application, such as Figure 6 As shown, a self-moving device (such as a lawn mower) walks along an initial boundary 61 to traverse a plurality of third boundary coordinates 62 .

[0088] Figure 6 In the embodiment, when the self-mobile device reaches the third boundary coordinate 62, the boundary outer area 63 corresponding to the third boundary coordinate 62 on the initial boundary 61 is determined, and the safety of the boundary outer area 63 is judged based on the operating data and environmental data at the third boundary coordinate 62. If it is a safe area, the self-mobile device is controlled to move outward from the third boundary coordinate 62 to the boundary outer area 63 based on the preset boundary optimization algorithm, and moves to the expanded boundary coordinate 64, and then moves from the expanded boundary coordinate 64 to the next third boundary coordinate 62.

[0089] It can be seen that in this embodiment, dynamic optimization from the initial boundary to the expanded boundary is achieved, ensuring that the mapping boundary fits the actual lawn range, improving mapping accuracy and the integrity of the equipment operation area, and at the same time ensuring the efficiency and continuity of the mapping process through orderly movement.

[0090] In a possible embodiment, generating the target boundary map based on the multiple expanded boundary coordinates includes: updating the multiple third boundary coordinates based on the multiple expanded boundary coordinates to obtain multiple target boundary coordinates corresponding one-to-one to the multiple third boundary coordinates; optimizing the initial boundary based on the multiple target boundary coordinates to obtain a target boundary area; and generating the target boundary map based on the target boundary area.

[0091] Specifically, for each third boundary coordinate, if the boundary expansion operation is successfully performed and the expanded boundary coordinate is determined, the expanded boundary coordinate is determined as the target boundary coordinate. As for the third boundary coordinate corresponding to the unsuccessful boundary expansion operation, the third boundary coordinate is directly determined as the target boundary coordinate.

[0092] In a possible embodiment, the method further includes: outputting the target boundary map; detecting a confirmation operation or a cancellation operation performed by the user on the target boundary map; and saving the target boundary map in response to the confirmation operation, or outputting a first prompt message in response to the cancellation operation to prompt the user to re-execute the mapping operation.

[0093] Furthermore, in a possible embodiment, the method also includes: detecting a modification operation performed by the user on the target boundary map; in response to the modification operation, outputting a recording report formed by the mobile device traversing the multiple third boundary coordinates, the recording report including a recorded video, key coordinate data, dangerous scene processing information, obstacle avoidance information, and user rescue information; generating and outputting second prompt information based on the recording report, the second prompt information including a boundary adjustment suggestion, the second prompt information being used to guide the user to adjust the target boundary area according to the boundary adjustment suggestion; and generating the latest ultimate boundary map in response to the user's adjustment operation on the target boundary area in the remote sensing image.

[0094] Specifically, see Figure 7 , Figure 7 This is a schematic diagram of a display interface of a target boundary map provided in an embodiment of the present application. Figure 7 As shown, in the target boundary map interface, the target boundary map is displayed.

[0095] Figure 7 The left side of the interface features a navigation bar with "Target Map" selected, displaying the target boundary map. Other navigation bars include "User Center," "Manual Mapping," "Vehicle Management," and "Terminal Management." The center grid map displays the target boundary map 71 (gray-filled portion). A pop-up window displays the message "For the target boundary map, please select:" and provides options for "Confirm," "Cancel," and "Modify," allowing users to confirm or adjust the generated target boundary map 71. The right side features "Record Report," "Map Storage," and "Map Update," allowing users to record, save, and subsequently update results, achieving closed-loop management of the mapping process.

[0096] It can be seen that in this embodiment, the map is saved by confirming the operation, and the boundary is readjusted by canceling or modifying the operation, thereby meeting the user's personalized needs for mapping results and improving interaction flexibility.

[0097] In one possible embodiment, generating the latest ultimate boundary map in response to the user's adjustment operation on the target boundary area in the remote sensing image includes: determining multiple expected boundary coordinates in response to the user's adjustment operation on the multiple target boundary coordinates in the remote sensing image, and generating an expected boundary map based on the multiple expected boundary coordinates; controlling the self-moving device to travel along the expected boundary and obtain expected driving data based on the expected boundary map; and updating the expected boundary map according to the expected driving data to obtain the ultimate boundary map.

[0098] It is understandable that when the user needs to adjust or modify the target boundary area, an adjustment operation needs to be performed to determine the expected boundary coordinates, and the operations of generating an initial boundary map + controlling the self-mobile device to drive + optimizing the map based on the driving data in the aforementioned method embodiment need to be repeated to obtain an optimized boundary map.

[0099] It can be seen that in this embodiment, the initial boundary is generated by the user manually selecting points, coordinate processing and legality verification, the control device traverses and collects data according to the optimized path, realizes boundary expansion and map update, supports user interactive verification, forms an efficient mapping closed loop, and improves accuracy and safety.

[0100] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the mobile electronic device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0101] In accordance with the above-mentioned embodiment, please refer to Figure 8 , Figure 8 This is a block diagram of the functional units of an automatic mapping device provided in an embodiment of the present application, such as Figure 8 As shown, the automatic mapping device includes: a response unit 801, which is used to generate an initial boundary map in response to multiple initial boundary coordinates selected by a user in a remote sensing map; an acquisition unit 802, which is used to control the mobile device to travel along the initial boundary and obtain target travel data based on the initial boundary map; and a processing unit 803, which is used to update the initial boundary map according to the target travel data to obtain a target boundary map.

[0102] In one embodiment, in terms of generating an initial boundary map in response to multiple initial boundary coordinates selected by a user in a remote sensing image, the response unit 801 is specifically used to: in response to the user's selection operation for the multiple initial boundary coordinates in the remote sensing image, perform a first preset operation on the multiple initial boundary coordinates to obtain multiple first boundary coordinates; perform a legitimacy judgment on the multiple first boundary coordinates based on a preset coordinate type to obtain a target judgment result, the coordinate type including a lawn type and a non-lawn type; perform a second preset operation based on the target judgment result to obtain multiple second boundary coordinates; and generate the initial boundary map based on the multiple second boundary coordinates.

[0103] In one embodiment, in terms of performing a first preset operation on the multiple initial boundary coordinates to obtain multiple first boundary coordinates, the response unit 801 is specifically used to: perform the coordinate simplification operation on the multiple initial boundary coordinates according to a preset coordinate simplification algorithm to simplify the continuous dense coordinates to obtain multiple reference boundary coordinates, where the reference boundary coordinates are pixel coordinates; perform the coordinate conversion operation according to a preset coordinate conversion algorithm to convert the multiple reference boundary coordinates into the multiple first boundary coordinates, where the first boundary coordinates are latitude and longitude coordinates.

[0104] In one embodiment, in terms of performing a legality judgment on the multiple first boundary coordinates based on a preset coordinate type to obtain a target judgment result, the response unit 801 is specifically used to: for each first boundary coordinate among the multiple first boundary coordinates, judge the coordinate type of the first boundary coordinate; if the coordinate type is a lawn type, the first judgment result is that the first boundary coordinate is a legal boundary coordinate; if the coordinate type is a non-lawn type, the second judgment result is that the first boundary coordinate is an illegal boundary coordinate.

[0105] In one embodiment, in terms of performing a second preset operation based on the target judgment result to obtain multiple second boundary coordinates, the response unit 801 is specifically used to: determine that the coordinates currently selected by the user are illegal boundary coordinates based on the second judgment result; perform the second preset operation to prompt the user to reselect boundary coordinates through a pop-up window; determine that the boundary coordinates reselected by the user are legal boundary coordinates; and determine all legal boundary coordinates selected by the user as the second boundary coordinates.

[0106] In one embodiment, the response unit 801 is also used to: determine the total number and point distribution status of the multiple second boundary coordinates; when it is detected that the total number of the multiple second boundary coordinates is less than a preset number threshold, and / or the point distribution status of the multiple second boundary coordinates is a collinear state, a third preset operation is executed to prompt the user to continue to supplement the selected boundary coordinates through a pop-up window.

[0107] In one embodiment, in terms of controlling the self-moving device to travel along the initial boundary and acquiring target driving data based on the initial boundary map, the acquisition unit 802 is specifically used to: control the self-moving device to travel along the initial boundary and acquire operating data during the driving process; control the self-moving device to spin and scan the surrounding environment when traveling to the third boundary coordinate to acquire environmental data; and determine the target driving data based on the operating data and the environmental data.

[0108] In one embodiment, in terms of controlling the self-moving device to travel along the initial boundary, the acquisition unit 802 is specifically used to: determine the third boundary coordinate among the multiple third boundary coordinates that is closest to the initial coordinate of the self-moving device; and control the self-moving device to travel along the initial boundary starting from the third boundary coordinate that is closest to the distance until traversing the multiple third boundary coordinates.

[0109] In one embodiment, in terms of updating the initial boundary map according to the target driving data to obtain the target boundary map, the processing unit 803 is specifically used to: when it is detected that the self-moving device travels to the third boundary coordinate, perform a boundary expansion operation according to the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate; when it is detected that the self-moving device has traversed the multiple third boundary coordinates, obtain multiple expanded boundary coordinates; and generate the target boundary map according to the multiple expanded boundary coordinates.

[0110] In one embodiment, in performing a boundary expansion operation based on the operating data and the environmental data of the self-mobile device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate, the processing unit 803 is specifically used to: determine the boundary outside area corresponding to the third boundary coordinate on the initial boundary; perform a safety judgment on the boundary outside area based on the operating data and the environmental data of the self-mobile device at the third boundary coordinate; if the boundary outside area is a safe area, control the self-mobile device to move outward from the third boundary coordinate to the boundary outside area and to the expanded boundary coordinate based on a preset boundary optimization algorithm to achieve boundary expansion.

[0111] In one embodiment, after performing a boundary expansion operation based on the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate, the processing unit 803 is further used to: control the self-moving device to continue moving from the expanded boundary coordinate to the next third boundary coordinate located on the initial boundary; when it is detected that the self-moving device has moved to the next third boundary coordinate, repeat the above-mentioned step of performing a boundary expansion operation based on the operating data and the environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the next third boundary coordinate.

[0112] In one embodiment, in terms of generating the target boundary map based on the multiple expanded boundary coordinates, the processing unit 803 is specifically used to: update the multiple third boundary coordinates based on the multiple expanded boundary coordinates to obtain multiple target boundary coordinates corresponding one-to-one to the multiple third boundary coordinates; optimize the initial boundary based on the multiple target boundary coordinates to obtain a target boundary area; and generate the target boundary map based on the target boundary area.

[0113] In one embodiment, the processing unit 803 is further used to: output the target boundary map; detect the user's confirmation operation or cancellation operation on the target boundary map; save the target boundary map in response to the confirmation operation, or output a first prompt message in response to the cancellation operation to prompt the user to re-execute the mapping operation.

[0114] In one embodiment, the processing unit 803 is further used to: detect the user's modification operation on the target boundary map; in response to the modification operation, output a recording report formed by the mobile device traversing the multiple third boundary coordinates, the recording report including recorded video, key coordinate data, dangerous scene processing information, obstacle avoidance information and user rescue information; generate and output second prompt information based on the recording report, the second prompt information including boundary adjustment suggestions, the second prompt information is used to guide the user to adjust the target boundary area according to the boundary adjustment suggestions; in response to the user's adjustment operation on the target boundary area in the remote sensing image, generate the latest ultimate boundary map.

[0115] In one embodiment, in terms of generating the latest ultimate boundary map in response to the user's adjustment operation on the target boundary area in the remote sensing image, the processing unit 803 is specifically used to: determine a plurality of expected boundary coordinates in response to the user's adjustment operation on the plurality of target boundary coordinates in the remote sensing image, and generate an expected boundary map based on the plurality of expected boundary coordinates; control the self-moving device to travel along the expected boundary and obtain expected driving data based on the expected boundary map; and update the expected boundary map according to the expected driving data to obtain the ultimate boundary map.

[0116] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part and will not be repeated here.

[0117] In the case of integrated units, such as Figure 9 As shown, Figure 9 This is a block diagram of the functional units of another automatic mapping device provided in an embodiment of the present application. Figure 9 In the embodiment, the automatic mapping device includes: a processing module 901 and a communication module 902. The processing module 901 is used to control and manage the actions of an automatic mapping device, for example, executing the steps of the response unit 801 and the processing unit 803, and / or other processes for executing the technology described herein. The communication module 902 is used to support the interaction between an automatic mapping device and other devices. Figure 9 As shown, the automatic mapping device may further include a storage module 903, which is used to store the program code and data of the automatic mapping device. Among them, the processing module 901 may be a processor or a controller, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute the various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessor, and so on. The communication module 902 may be a transceiver, an RF circuit or a communication interface, etc. The storage module 903 may be a memory. Among them, all relevant contents of each scenario involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here. The above automatic mapping devices can all execute the above Figure 4 The automatic mapping method shown.

[0118] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in accordance with the embodiments of this application are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0119] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0120] The present application also provides a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may comprise an electronic device.

[0121] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the 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 the present application.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed methods, devices, and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the units is merely a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical, or other forms.

[0123] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0124] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may be physically included separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional units.

[0125] The above-mentioned integrated unit implemented as a software functional unit can be stored in a computer-readable storage medium. The software functional unit is stored in a storage medium and includes instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform some of the steps of the method described in various embodiments of the present invention. The aforementioned storage medium includes a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a volatile memory, or a non-volatile memory. The non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DRRAM). Various media can store program code.

[0126] Although the present invention is disclosed above, it is not limited thereto. Any person skilled in the art may readily conceive of variations or substitutions, and may make various modifications and alterations without departing from the spirit and scope of the present invention. Combinations of the above-described functions and implementation steps, including software and hardware implementations, are all within the scope of protection of the present invention.

Claims

1. An automatic mapping method, characterized in that: include: generating an initial boundary map in response to a plurality of initial boundary coordinates selected by a user in the remote sensing image; Control the mobile device to travel along the initial boundary and obtain operating data during the travel process; Controlling the self-moving device to spin and scan the surrounding environment when traveling to a third boundary coordinate to obtain environmental data, wherein the initial boundary includes a plurality of third boundary coordinates; determining target driving data according to the operating data and the environmental data; When it is detected that the self-moving device has traveled to the third boundary coordinate, performing a boundary expansion operation based on the operation data and environment data of the self-moving device at the third boundary coordinate to determine an expanded boundary coordinate corresponding to the third boundary coordinate; When it is detected that the self-moving device has traversed the plurality of third boundary coordinates, a plurality of expanded boundary coordinates are obtained; A target boundary map is generated according to the plurality of expanded boundary coordinates.

2. The method according to claim 1, characterized in that The generating of the initial boundary map in response to a plurality of initial boundary coordinates selected by the user in the remote sensing image comprises: In response to a selection operation by the user on the plurality of initial boundary coordinates in the remote sensing image, performing a first preset operation on the plurality of initial boundary coordinates to obtain a plurality of first boundary coordinates; Performing a validity judgment on the plurality of first boundary coordinates based on a preset coordinate type to obtain a target judgment result, wherein the coordinate type includes a lawn type and a non-lawn type; Perform a second preset operation according to the target judgment result to obtain a plurality of second boundary coordinates; The initial boundary map is generated according to the plurality of second boundary coordinates.

3. The method according to claim 2, characterized in that The first preset operation includes a coordinate simplification operation and a coordinate conversion operation; performing the first preset operation on the multiple initial boundary coordinates to obtain multiple first boundary coordinates includes: Performing the coordinate simplification operation on the multiple initial boundary coordinates according to a preset coordinate simplification algorithm to simplify the continuous dense coordinates to obtain a plurality of reference boundary coordinates, where the reference boundary coordinates are pixel coordinates; The coordinate conversion operation is performed according to a preset coordinate conversion algorithm to convert the plurality of reference boundary coordinates into the plurality of first boundary coordinates, where the first boundary coordinates are latitude and longitude coordinates.

4. The method according to claim 2, characterized in that The actual geographical scene corresponding to the lawn type characterization coordinates is lawn, and the actual geographical scene corresponding to the non-lawn type characterization coordinates is non-lawn; The performing of a validity judgment on the plurality of first boundary coordinates based on a preset coordinate type to obtain a target judgment result includes: For each first boundary coordinate of the plurality of first boundary coordinates, determining a coordinate type of the first boundary coordinate; If the coordinate type is a lawn type, the first judgment result is that the first boundary coordinate is a legal boundary coordinate; If the coordinate type is a non-lawn type, the second judgment result is that the first boundary coordinate is an illegal boundary coordinate.

5. The method according to claim 4, characterized in that The performing of a second preset operation according to the target determination result to obtain a plurality of second boundary coordinates includes: Determining, according to the second judgment result, that the coordinates currently selected by the user are illegal boundary coordinates; executing the second preset operation to prompt the user to reselect boundary coordinates through a pop-up window; Determining that the boundary coordinates reselected by the user are legal boundary coordinates; All legal boundary coordinates selected by the user are determined as the second boundary coordinates.

6. The method according to claim 5, characterized in that The method further comprises: Determining the total number and point distribution status of the plurality of second boundary coordinates; When it is detected that the total number of the multiple second boundary coordinates is less than a preset number threshold, and / or the point distribution state of the multiple second boundary coordinates is a collinear state, a third preset operation is performed to prompt the user through a pop-up window to continue to select additional boundary coordinates, and the multiple third boundary coordinates are obtained by performing the fourth preset operation on the multiple second boundary coordinates.

7. The method according to claim 6, characterized in that The controlling the mobile device to travel along the initial boundary includes: Determining a third boundary coordinate that is closest to the initial coordinates of the self-moving device among the plurality of third boundary coordinates; The self-moving device is controlled to travel along the initial boundary starting from the third boundary coordinate that is closest to the self-moving device until the plurality of third boundary coordinates are traversed.

8. The method according to claim 7, characterized in that The performing a boundary expansion operation based on the operation data and environment data of the mobile device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate includes: Determine the outer boundary area corresponding to the third boundary coordinate on the initial boundary; Performing a safety assessment on the area outside the boundary based on the operation data and the environmental data of the mobile device at the third boundary coordinate; If the outer boundary area is a safe area, the self-moving device is controlled to move outward from the third boundary coordinate to the outer boundary area based on a preset boundary optimization algorithm, and then move to the expansion boundary coordinate to achieve boundary expansion.

9. The method according to claim 8, characterized in that After performing a boundary expansion operation based on the operation data and environment data of the mobile device at the third boundary coordinate to determine an expanded boundary coordinate corresponding to the third boundary coordinate, the method further includes: Controlling the self-moving device to continue moving from the expanded boundary coordinate to a next third boundary coordinate located on the initial boundary; When it is detected that the self-moving device travels to the next third boundary coordinate, the above-mentioned step of performing the boundary expansion operation according to the operating data and environmental data of the self-moving device at the third boundary coordinate is repeated to determine the expanded boundary coordinate corresponding to the next third boundary coordinate.

10. The method according to claim 1, characterized in that Generating a target boundary map according to the plurality of expanded boundary coordinates includes: updating the plurality of third boundary coordinates according to the plurality of expanded boundary coordinates to obtain a plurality of target boundary coordinates corresponding one-to-one to the plurality of third boundary coordinates; Optimizing the initial boundary according to the multiple target boundary coordinates to obtain a target boundary area; The target boundary map is generated according to the target boundary area.

11. The method according to claim 10, characterized in that The method further comprises: outputting the target boundary map; detecting a confirmation operation or a cancellation operation of the user on the target boundary map; In response to the confirmation operation, the target boundary map is saved, or in response to the cancellation operation, a first prompt message is output to prompt the user to re-execute the mapping operation.

12. The method according to claim 11, characterized in that The method further comprises: detecting a modification operation performed by the user on the target boundary map; In response to the modification operation, outputting a recording report formed by the mobile device traversing the plurality of third boundary coordinates, the recording report including recorded video, key coordinate data, dangerous scene processing information, obstacle avoidance information, and user rescue information; generating and outputting second prompt information according to the recording report, the second prompt information including a boundary adjustment suggestion, the second prompt information being used to guide the user to adjust the target boundary area according to the boundary adjustment suggestion; In response to the user's adjustment operation on the target boundary area in the remote sensing image, an updated ultimate boundary map is generated.

13. The method according to claim 12, characterized in that The step of generating the latest ultimate boundary map in response to the user's adjustment operation on the target boundary area in the remote sensing image comprises: In response to the user's adjustment operation on the plurality of target boundary coordinates in the remote sensing image, determining a plurality of expected boundary coordinates, and generating an expected boundary map according to the plurality of expected boundary coordinates; controlling the mobile device to travel along the expected boundary based on the expected boundary map and acquiring expected travel data; The expected boundary map is updated according to the expected driving data to obtain the ultimate boundary map.

14. The method according to claim 1, wherein The self-moving device is configured with a multimodal perception system, and the multimodal perception system is used to control the self-moving device to execute a dangerous scene processing strategy and an obstacle avoidance strategy during driving; The dangerous scene processing strategy includes a first processing strategy and a second processing strategy, and the dangerous scene processing strategy is used to control the self-mobile device to execute a corresponding control strategy when identifying dangerous scenes with different danger levels in the front area; The obstacle avoidance strategy includes a static obstacle avoidance strategy, a low-speed obstacle avoidance strategy, and a high-speed obstacle avoidance strategy. The obstacle avoidance strategy is used to control the self-moving device to execute a corresponding control strategy based on the movement state of the obstacle when it identifies that there is an obstacle in the front area.

15. The method according to claim 14, characterized in that The danger level of the dangerous scene corresponding to the first processing strategy is higher than the danger level of the dangerous scene corresponding to the second processing strategy; The first processing strategy is to control the self-moving device to stop driving and generate a first alarm message to prompt the user to implement rescue; The second processing strategy is to control the mobile device to slow down to a target speed, perform a visual scan for a preset time, start a high-frequency sampling mode, and generate a second alarm message.

16. The method according to claim 15, characterized in that The static obstacle avoidance strategy is to record the coordinates of the obstacle and plan a detour route based on the obstacle coordinates, and then control the mobile device to continue traveling according to the detour route; The low-speed obstacle avoidance strategy is to control the self-moving device to emit an audible and visual warning within a preset time period, and at the same time control the self-moving device to travel at a low speed or stop traveling; The high-speed obstacle avoidance strategy is to control the self-moving device to emergency brake and reverse for a preset distance before stopping when it is detected that the expected moving trajectory of the high-speed obstacle intersects with the expected driving trajectory of the self-moving device, and to generate a third alarm message to prompt the user to implement rescue.

17. An automatic mapping device, characterized in that: The device comprises: a response unit for generating an initial boundary map in response to a plurality of initial boundary coordinates selected by a user in the remote sensing map; an acquisition unit, configured to control the self-moving device to travel along an initial boundary and acquire operating data during the travel; control the self-moving device to spin and scan the surrounding environment when traveling to a third boundary coordinate to acquire environmental data, wherein the initial boundary includes a plurality of third boundary coordinates; and determine target travel data based on the operating data and the environmental data; The processing unit is configured to, when detecting that the self-moving device has traveled to the third boundary coordinate, perform a boundary expansion operation based on the operating data and environmental data of the self-moving device at the third boundary coordinate to determine the expanded boundary coordinate corresponding to the third boundary coordinate; obtain multiple expanded boundary coordinates when detecting that the self-moving device has traversed the multiple third boundary coordinates; and generate a target boundary map based on the multiple expanded boundary coordinates.

18. A self-propelled device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the processor calls the computer program in the memory, the step instructions in the method according to any one of claims 1 to 16 are executed.

19. A terminal device, characterized in that: The terminal device is connected to the mobile device for communication, and the terminal device includes: one or more processors; One or more memories for storing programs, The one or more memories and the program are configured so that the one or more processors control the terminal device to execute the steps in the method according to any one of claims 1 to 16.

20. A computer-readable storage medium, characterized in that A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 16.

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