Method for mapping target area, and related apparatus

Abstract

A method for mapping a target area, and a related apparatus. The method comprises: a robot acquires a path, wherein the path passes through a non-working area and m working areas in a target area; and the robot moves along the path, during the movement, when it is determined that the position of the robot is located in one of the working areas and mapping of the working area has not been completed, the working area being mapped, and when it is determined that the position of the robot is located in the non-working area, or the position of the robot is located in the working area and the mapping of the working area has been completed, the robot continuing moving along the path. According to the method, a user only needs to participate in the process of acquiring a path by a robot, and a subsequent mapping process is autonomously completed by the robot, thereby greatly reducing the waiting time of the user and improving user experience.

Description

A method and related apparatus for mapping a target area

[0001] This application claims priority to Chinese Patent Application No. 202411813628.3, filed on December 10, 2024, entitled "A Method and Related Apparatus for Mapping a Target Area", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of computer technology, and in particular to a method and related apparatus for mapping a target area. Background Technology

[0003] With the continuous advancement of technology, robots are playing an increasingly important role in modern home and work environments. For example, lawnmower robots can autonomously complete tasks such as mowing and charging, requiring almost no user intervention, thus greatly improving the convenience of daily life. However, before a robot can begin performing a specific task, it typically needs to create a map of multiple work areas. This process is crucial for the robot's autonomous operation, ensuring that it accurately identifies its environment, avoids obstacles, and effectively completes its tasks.

[0004] In existing technologies, the process of a robot building maps across multiple areas is as follows: First, the user controls the robot to move to the first work area, where the robot collects environmental information and builds a map of that work area based on this information. Then, the user controls the robot to move from the first work area to the second work area, where the robot collects environmental information and builds a map of that area based on this information. This process is repeated until the robot has completed map building for all work areas.

[0005] However, in the existing technology, this operation mode requires the user to participate in the entire process of map building of the work area, which is relatively cumbersome, resulting in long waiting times and poor user experience. Summary of the Invention

[0006] This application provides a method and related apparatus for mapping a target area, which can reduce user waiting time and improve user experience.

[0007] In a first aspect, embodiments of this application provide a method for mapping a target region, the target region comprising m working regions, where m is any positive integer greater than 1, the method comprising:

[0008] The robot obtains a path, which passes through m disconnected working areas in the non-working area and the target area;

[0009] The robot moves along the path. During the movement: if the robot's position is determined to be in one of the working areas and the working area has not been mapped, the working area is mapped; if the robot's position is determined to be in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0010] In the above solution, firstly, the robot acquires a path that passes through m working areas within the non-working area and the target area. Then, the robot moves along the path. During movement, if the robot's position is determined to be within one of the working areas and the area is not yet mapped, the working area is mapped. If the robot's position is determined to be within a non-working area, or if the robot's position is within a working area and the area is already mapped, the robot continues moving along the path. Compared to existing solutions where the user needs to participate in the entire mapping process until all m working areas are mapped before leaving, this solution only requires the user to participate in the robot's path acquisition process; the subsequent mapping process is completed autonomously by the robot. This significantly reduces user waiting time and improves the user experience.

[0011] Based on the first aspect, among the possible implementation methods, the robot acquisition path includes:

[0012] The robot receives instructions from the remote control device, moves in response to the instructions, and collects multiple location points along the way, thus obtaining a path based on these location points.

[0013] In the above scheme, the robot obtains its path as follows: the robot receives instructions from the remote control device, moves accordingly, and collects multiple location points it traverses. Based on these location points, it then obtains the path. In this way, the robot can quickly obtain a path that traverses m work areas, saving time. Furthermore, users can flexibly adjust the robot's movement according to actual conditions, making the obtained path more accurate and improving the efficiency of subsequent mapping tasks.

[0014] Based on the first aspect, in possible implementations, the process of the robot moving along the path is as follows:

[0015] The robot moves along the path from the end point of the path to the beginning point of the path. The end point of the path is the destination reached in response to the command, and the beginning point of the path is the starting point of the movement in response to the command.

[0016] Based on the first aspect, in possible implementations, the starting point of the path is the location of the charging pile, and the ending point of the path is any location within the last work area traversed by the path.

[0017] It's understandable that setting the starting point of the path to the location of the charging station ensures the robot is fully charged before starting the task, guaranteeing sufficient power throughout the task and preventing interruptions or reduced efficiency due to insufficient power. Setting the ending point of the path to any location within the last work area traversed allows the robot to remain within that area, saving mapping time.

[0018] Based on the first aspect, in possible implementations, determining the robot's position within one of the work areas during movement includes:

[0019] During the movement, the robot acquires environmental information and determines its position within one of the work areas based on this information.

[0020] In the above solution, by acquiring environmental information, the robot can accurately identify whether its current location is within the work area, avoiding wasting time mapping in non-work areas. This helps improve the efficiency and accuracy of mapping tasks, ensuring that the robot performs corresponding operations within the actual work area where mapping is needed, saving resources and time costs. Secondly, by using environmental information to determine whether the current location is within the work area, the robot can flexibly adjust its action strategy according to the actual situation, avoiding resource waste caused by mapping operations in non-work areas. This intelligent location confirmation method enhances the robot's autonomy and intelligence, enabling it to execute tasks more intelligently, improving task execution efficiency and success rate.

[0021] Based on the first aspect, in possible implementations, the process of determining the robot's location within one of the work areas based on environmental information is as follows:

[0022] The robot identifies the boundaries of the work area based on environmental information, determines the intersection of the boundary and the path, and if the robot reaches the intersection, it is determined that the robot's position is in one of the work areas.

[0023] Based on the first aspect, in possible implementations, when the robot's position is determined to be within one of the work areas and the work area has not yet been mapped, the process of mapping the work area is as follows:

[0024] If the robot is located in one of the work areas and the work area has not been mapped, the robot can move autonomously within the work area to explore and map the work area.

[0025] Based on the first aspect, in possible implementations, when the robot's position is determined to be within a work area and the work area has not yet been mapped, after mapping the work area, the method further includes:

[0026] The robot determines the first intersection point between the path and the work area, and moves to the position of the first intersection point. The first intersection point is the first intersection point in the work area that the robot passes through during its movement from the starting point of the path to the ending point of the path.

[0027] The robot continues to move along the path towards the starting point. During the movement, if the robot's position is determined to be in one of the working areas and the working area has not been mapped, the working area is mapped. If the robot's position is determined to be in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0028] Repeat the above steps until the robot moves to the starting point of the path.

[0029] It should be understood that moving the robot to the first intersection point between the path and the work area (the first intersection point the robot passes through during its movement from the starting point to the ending point of the target area) ensures that the robot can smoothly return to the path to continue its mapping task after leaving the currently mapped work area. This method effectively plans the robot's movement trajectory, avoiding getting lost or wasting time between work areas, and improving the continuity and efficiency of task execution. Secondly, by moving to the first intersection point between the path and the work area, the robot can promptly identify and enter the next work area to be mapped while continuing to move along the path towards the starting point of the target area, accurately executing the mapping task. This precise position adjustment method helps the robot complete the mapping task efficiently, avoiding duplicate or missed mapping, and improving the accuracy and completeness of task execution.

[0030] Based on the first aspect, in possible implementations, the process of the robot acquiring a path includes:

[0031] The robot obtains the path from an external device, where the path is collected by the external device.

[0032] It should be understood that when the robot obtains a path from an external device, the user can remain completely uninvolved in the robot's mapping process, reducing the user's waiting time.

[0033] Based on the first aspect, in possible implementations, the m work areas have no direct connection or overlap, and the robot moves from one work area through a non-work area to another work area.

[0034] Based on the first aspect, in possible implementations, the instructions received by the robot from the remote control device include at least one of the following: moving forward, moving backward, moving left, moving right, stopping, accelerating, and decelerating.

[0035] Based on the first aspect, among possible implementation methods, environmental information includes visual information or lidar data.

[0036] Based on the first aspect, in a possible implementation, after the robot completes the mapping of m work areas, it calculates the intersection point of each work area with the path, and extracts the path between the intersection points from the path as the connecting path connecting the two work areas.

[0037] Secondly, embodiments of this application provide an apparatus for mapping a target region, the target region comprising m working regions, where m is any positive integer greater than 1, including:

[0038] The acquisition module is used to acquire the path, where the path passes through m working areas in the non-working area and the target area;

[0039] The determination module is used to determine if the robot's position is in one of the working areas and the working area has not been mapped, and to map the working area. If the robot's position is in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0040] Based on the second aspect, in possible implementations, the acquisition module is used for:

[0041] It receives instructions from the remote control device, responds to the instructions to move and collect multiple location points passed by the robot, and obtains the path based on the multiple location points.

[0042] Based on the second aspect, in a possible implementation, the robot moves along a path from the end point of the path to the beginning point of the path, where the end point of the path is the destination reached in response to the command, and the beginning point of the path is the starting point of the movement in response to the command.

[0043] Based on the second aspect, in possible implementations, the starting point of the path is the location of the charging pile, and the ending point of the path is any location within the last work area traversed by the path.

[0044] Based on the second aspect, among the possible implementations, the module is used for:

[0045] During the movement, the robot acquires environmental information and determines its position within one of the work areas based on this information.

[0046] Based on the second aspect, in possible implementations, the determining module is used to: identify the boundary of the work area based on environmental information, determine the intersection of the boundary and the path, and if the robot reaches the intersection, determine that the robot's position is located in one of the work areas.

[0047] Based on the second aspect, in a possible implementation, the determining module is used to: when the robot's position is determined to be within one of the work areas and the work area has not yet been mapped, the robot autonomously moves within the work area to explore and map the work area. Based on the second aspect, in a possible implementation, the determining module is used to:

[0048] The first intersection point between the path and the work area is determined, and the robot moves to the position of the first intersection point. The first intersection point is the first intersection point in the work area that the robot passes through during its movement from the starting point of the path to the ending point of the path.

[0049] The robot continues to move along the path towards the starting point. During the movement, if the robot's position is determined to be in one of the working areas and the working area has not been mapped, the working area is mapped. If the robot's position is determined to be in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0050] Repeat the above steps until the robot moves to the starting point of the path.

[0051] Based on the second aspect, in a possible implementation, the robot obtains the path from an external device, wherein the path is collected by the external device.

[0052] The various functional modules in the second aspect are used to implement the methods described in the first aspect and the possible implementation methods of the first aspect.

[0053] Based on the second aspect, in possible implementations, the m work areas have no direct connection or overlap, and the robot moves from one work area through a non-work area to another work area.

[0054] Based on the second aspect, in possible implementations, the instructions received by the acquisition module from the remote control device include at least one of the following: a forward movement instruction, a backward movement instruction, a left movement instruction, a right movement instruction, a stop instruction, an acceleration instruction, and a deceleration instruction.

[0055] Based on the second aspect, among possible implementation methods, environmental information includes visual information or lidar data.

[0056] Based on the second aspect, in a possible implementation, the determining module is also used to: after completing the mapping of m work areas, calculate the intersection point of each work area with the path, and extract the path between the intersection points from the path as the connecting path connecting the two work areas.

[0057] Thirdly, embodiments of this application provide a computer storage medium including program instructions that, when executed by a robot, cause the robot to perform the method described in the first aspect and any possible implementation thereof.

[0058] Fourthly, this application provides a computer program product, including program instructions, which, when executed by a robot, enables the robot to perform the aforementioned first aspect and any possible implementation thereof. The computer program product can be a software installation package; when the method provided by any possible design of the aforementioned first aspect is required, the computer program product can be downloaded and executed on the robot to implement the first aspect and any possible implementation thereof.

[0059] Fifthly, this application provides a robot including program instructions that, when executed by the robot, cause the robot to perform the method described in the first aspect and any possible implementation thereof. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0061] Figure 1 is a flowchart illustrating a method for mapping a target area provided in this application;

[0062] Figure 2 is a schematic diagram of the structure of a target region provided in this application;

[0063] Figure 3 is a schematic diagram of the structure of another target region provided in this application;

[0064] Figure 4 is a schematic diagram of the structure of a device for mapping a target area provided in this application;

[0065] Figure 5 is a schematic diagram of the structure of a computing device provided in this application. Detailed Implementation

[0066] The embodiments of this application are described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0067] It should be noted that the terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0068] It should be noted that, when used in this specification and the appended claims, the term "comprising" and any variations thereof are intended to cover a non-exclusive inclusion. For example, a system, product, or apparatus that comprises a series of units / devices is not limited to the units / devices listed, but may optionally include units / devices not listed, or may also optionally include other units / devices inherent in such products or apparatuses.

[0069] This application provides a method for mapping a target area. The target area comprises m disconnected work areas. The target area can be different types of locations, such as hospitals, schools, and playgrounds, etc., and this application does not impose any specific limitations. The work areas can be specific areas within these locations, such as lawns, etc., and this application does not impose any specific limitations. This application uses a lawn as the work area and a lawnmower robot as an example for illustration.

[0070] Referring to Figure 1, which is a flowchart of a method for mapping a target area provided in this application, the method includes, but is not limited to, the following description.

[0071] S101, Robot obtains path.

[0072] The path is the trajectory the robot will take when it subsequently maps the target area. This path will pass through non-working areas and m working areas within the target area, where m is any positive integer greater than 1.

[0073] The *m* working areas are m independent working areas within the target area, and these working areas have no direct connection or overlap. In other words, these working areas are independent of each other; the robot will not move directly from one working area to another, but must pass through non-working areas within the target area to reach another working area. The size and shape of the *m* working areas can be the same or different, and this application does not impose specific limitations. The working areas can be regular shapes, such as rectangles, squares, and circles, or they can be irregular shapes.

[0074] The process by which the robot obtains the path is as follows:

[0075] (1) The user sends commands to the robot through a remote control device, and the robot moves remotely. It moves from the beginning of the path to the end of the path.

[0076] In this embodiment, the remote control device can be various smart devices such as mobile phones, remote control handles, and tablets. Users can choose a suitable remote control device to control the robot according to their own needs and habits.

[0077] In this embodiment, the robot and the remote control device can be connected wirelessly, and the wireless connection can be at least one of Bluetooth, infrared, Wi-Fi, or data traffic.

[0078] Users can control the robot's direction and speed of movement as needed. Therefore, commands can include movement commands in four directions: forward, backward, left, and right, as well as commands such as stop, accelerate, and decelerate. This application does not impose specific limitations on the commands.

[0079] It should be noted that when a user controls the robot's movement using a remote control device, the device can provide guidance and prompts to help the user operate the robot correctly, guiding it through the m work areas within the target area. Through the prompts on the remote control device, the user can understand how to control the robot's movement, including how to adjust direction, speed, and stop. In this way, even if the user is not very familiar with the remote control device, they can easily guide the robot through the m work areas within the target area, completing the robot's path acquisition task.

[0080] (2) The robot receives instructions from the remote control device and moves in response to the instructions. During the movement, the robot collects the coordinates of multiple location points it passes through and obtains a path through the non-working area and m working areas in the target area through the multiple location points.

[0081] During movement, robots can use real-time kinematic (RTK) positioning to determine their location and obtain coordinates from multiple points. An RTK positioning system consists of a base station and a rover station. The base station receives satellite signals, measures errors, and sends correction information to the rover station. The rover station receives the correction information from the base station to improve positioning accuracy. RTK positioning utilizes the phase information of satellite signals, achieving centimeter-level or even millimeter-level high-precision positioning, making it suitable for scenarios requiring high-precision positioning. Besides RTK positioning, other systems such as the Global Positioning System (GPS) and Global Navigation Satellite System (GNSS) can also be used; this application does not specifically limit the applications.

[0082] The starting and ending points of the path can be any location within the target area, but they cannot be the same location. For example, the starting point can be the location of a charging station, which can be located on or outside the work area boundary. The ending point can be any location within the last work area traversed by the path. This application does not specifically limit the exact locations of the starting and ending points of the path.

[0083] It should be noted that once the robot obtains the path, the user can leave. The robot will then autonomously map the target area based on the obtained path, without any user intervention.

[0084] Referring to Figure 2, which is a schematic diagram of the target area provided in this application, the target area in Figure 2 includes three non-connected working areas: the first working area, the second working area, and the third working area. The starting point of the path is the location of the charging pile, which is located outside the working area. The ending point of the path is any location within the third working area, which is the last working area traversed by the path. In Figure 2, the intersection point of the path with the third working area is intersection point 1. There are two intersection points with the second working area, namely intersection points 2 and 3, and two intersection points with the first working area, namely intersection points 4 and 5.

[0085] Referring to Figure 3, which is a schematic diagram of another target area structure provided in this application, the target area in Figure 3 includes three non-connected working areas: the first working area, the second working area, and the third working area. The starting point of the path is the location of the charging pile, which is located on the boundary of the working area. The ending point of the path is any location within the third working area, which is the last working area traversed by the path. In Figure 3, the intersection point of the path with the third working area is intersection point 1, the intersection points with the second working area are two, namely intersection points 2 and 3, and the intersection point with the first working area is intersection point 4.

[0086] In one possible implementation, the robot acquires the path as follows: the user obtains path information through a non-working area and m working areas in the target area via other external devices. This path is collected by the external devices, and then the path information is transmitted to the robot through programming or other means, so that the robot can acquire the path and complete the subsequent mapping work of the target area.

[0087] S102. The robot moves along the acquired path. During the movement, it is determined whether the robot's position is within the work area.

[0088] The robot moves along the acquired path from the end point to the beginning point. During this movement, the robot can use sensors to acquire environmental information and determine whether its current position is within the work area. Environmental information refers to various sensory data surrounding the robot, including but not limited to visual information and LiDAR data. When the environmental information is visual, the sensor can be a camera, such as a binocular camera or a regular webcam; this application does not impose specific limitations. When the environmental information is LiDAR data, the sensor can be a LiDAR, such as a mechanical LiDAR, a solid-state LiDAR, or a millimeter-wave radar; this application does not impose specific limitations.

[0089] In one possible implementation, the robot can move along a learned path from its starting point to its ending point. During this movement, the robot can use sensors to acquire environmental information and determine whether its current position is within the work area based on this information. This application does not specifically limit the direction in which the robot moves along the learned path.

[0090] In one implementation, the environmental information acquired by the robot either includes only information about the work area or only information about the non-work area. In this case, the robot can use different features in the environmental information to determine whether its current position is within the work area. For example, the robot can determine whether its current position is within the work area based on color features in the environmental information. When the work area is a lawn, it usually has a distinct green characteristic, especially on sunny days, where the color is a uniform green or may contain different shades of green. The color of the non-work area is usually different from the work area; it may be gray roads, red bricks, etc., which usually contrast sharply with the green of the work area. When using color features in the environmental information for judgment, the robot can use parameters such as the red-green-blue (RGB) color space and the hue-saturation-value (HSV) color space to determine whether its current position is within the work area. This application does not specifically limit the parameters for measuring color features. As another example, the robot can determine whether its current position is within the work area based on texture features in the environmental information. When the work area is a lawn, its surface typically exhibits natural, irregular textures, such as fine stripes of grass blades, subtle undulations, and a relatively uniform surface. The texture of non-work areas usually differs from that of the work area. When non-work areas are roads, buildings, etc., the surface is typically smoother and more regular, and may possess obvious artificial design features, such as asphalt pavement or brick textures. When using texture features from environmental information for judgment, the robot can determine whether its current position is within the work area by using parameters such as texture roughness, local contrast, and directional features. This application does not specifically limit the parameters for measuring texture features.

[0091] It should be noted that the robot can also determine its current position by combining color and texture features from environmental information. The robot can also utilize machine learning or deep learning models, trained using environmental information from labeled work and non-work areas, allowing the model to learn more complex features of the work area. After training, the robot inputs the environmental information into the trained model (e.g., a convolutional neural network, CNN), and the model determines whether the robot's current position is within the work area based on the learned features. This application does not specifically limit the method by which the robot determines whether its position is within the work area.

[0092] In one specific embodiment, the robot is a lawnmower robot, the working area is a lawn, the non-working area is a road, the sensor is a camera, and the environmental information includes images of the ground surface. During movement, the lawnmower robot activates its camera to capture images of the ground surface. Then, based on its current position information, the lawnmower robot can obtain the area within the captured ground surface image. Next, the lawnmower robot can use a gray-level co-occurrence matrix (GLCM) to calculate the texture features of the area within the captured ground surface image. Typically, lawn textures exhibit high contrast and a certain directionality (the arrangement of grass blades), while road textures are usually more uniform and have lower local contrast. Finally, by analyzing the GLCM, the lawnmower robot can determine whether its position is within the working area.

[0093] In another implementation, the environmental information includes both the working area and the non-working area. In this case, the robot identifies the boundary of the working area based on the environmental information and determines the intersection of that boundary with the path. If the robot reaches that intersection, it is determined that the robot's position is within one of the working areas.

[0094] S103. If it is determined that the robot's position is in a non-working area, the robot continues to move along the path.

[0095] S104. If the robot's position is determined to be within the work area, the robot determines whether the work area has been mapped.

[0096] Specifically, assuming the robot's location is within the work area, the robot first obtains its current coordinates using localization technology. Next, the robot checks if its current location is within an existing map. This existing map is typically stored in a specific format, such as a raster map, topological map, or point cloud map. If the existing map is a raster map, the robot calculates whether its current coordinates are within a valid area of ​​the map or within a known occupied area. For example, it checks whether the cell at position (x, y) is marked as "occupied." If the existing map is a point cloud map, the robot matches its current coordinates with known point cloud data. Point cloud matching algorithms, such as the Iterative Closest Point (ICP) algorithm, are generally used to determine if the current location is close to existing map points. Finally, based on the results, the robot determines whether the work area has been successfully mapped.

[0097] It should be understood that the above method for determining whether the work area has been mapped is only a specific example. In practical applications, it can also be achieved in other ways, and this application does not make any specific limitations.

[0098] S105. If it is determined that the robot's position is within the work area and the work area has been mapped, the robot continues to move along the path.

[0099] S106. If it is determined that the robot's position is in the work area and the work area has not been mapped, the robot maps the work area.

[0100] If the robot's location is determined to be within the work area, and the work area has not yet been mapped, the robot needs to map the work area. The specific steps are as follows:

[0101] (1) Robots need to collect data about their surroundings using onboard sensors (such as lidar, cameras, etc.). Sensors can acquire data such as ground height, obstacle locations, and the outline of the work area.

[0102] (2) The robot needs to extract features from the data obtained by the sensors to identify features such as the boundaries of the work area, the location of obstacles, and the ground height.

[0103] (3) Based on sensor data and feature extraction results, the robot can build an initial map of the work area.

[0104] (4) The robot needs to plan its movement path within the work area to ensure that it can cover the entire work area and acquire more data. Path planning can be performed using map-based algorithms, such as the A* algorithm and Dijkstra's algorithm.

[0105] (5) The robot moves along the planned path within the work area while continuously collecting sensor data. During the movement, it continuously updates map information, including the shape of the work area and the location of obstacles.

[0106] (6) Robots can use the simultaneous localization and mapping (SLAM) algorithm to optimize existing maps, improving the accuracy and completeness of the maps. Specifically, the SLAM algorithm can update the map and the robot's localization information simultaneously based on sensor data and the robot's motion trajectory.

[0107] (7) The robot saves the optimized map of the work area for subsequent work.

[0108] It should be understood that the above-described method of mapping the work area by the robot is merely a specific example. In practical applications, it can also be achieved in other ways, and this application does not impose any specific limitations.

[0109] After the robot completes the mapping of the work area, it executes S107.

[0110] S107. The robot determines the first intersection point between the path and the work area, and moves to the position of the first intersection point.

[0111] The first intersection point is the first point in the work area that the robot passes through during its movement from the start point to the end point of the path. For example, when the work area is the third area in Figure 2 or Figure 3, the first intersection point in the third work area that the robot passes through during its movement from the start point to the end point of the target area is intersection point 1. As another example, when the work area is the second area in Figure 2 or Figure 3, the first intersection point in the second work area that the robot passes through during its movement from the start point to the end point of the path is intersection point 3.

[0112] The process by which the robot determines the coordinates of the first intersection point between the path and the work area is as follows: First, the robot obtains the boundary information of the work area based on the map. Then, the robot calculates the intersection points of the path and the work area boundary using geometric methods, obtaining the coordinates of these intersection points. The robot stores the path information and the map of the work area. Finally, the robot determines the number of intersection points between the path and the work area boundary. If there is only one intersection point, its coordinates are the coordinates of the first intersection point. If there are two intersection points, the coordinates of the intersection point where the robot moves away from the current work area along the path's starting direction are selected as the coordinates of the first intersection point.

[0113] It should be understood that the method described above for the robot to determine the coordinates of the first intersection point between the path and the work area is merely a specific example. In practical applications, it can be achieved in other ways, and this application does not impose any specific limitations.

[0114] It should be noted that after obtaining the coordinates of the first intersection point, the robot moves to that point. The robot continues to move along the path towards the starting point of the target area. During the movement, steps S102 to S107 are selectively executed until the robot reaches the starting point of the target area, completing the mapping of m work areas. Furthermore, when the starting point of the path is a charging station, the robot can begin charging upon reaching the starting point.

[0115] In one specific embodiment, the robot first acquires the path information shown in Figure 2. Then, the robot completes the mapping of the target area in Figure 2 according to the following steps: First, the robot maps the third working area and moves to the first intersection point between the path and the third working area, i.e., intersection point 1. Next, the robot continues to move along the path, and after reaching intersection point 2, it autonomously maps the second working area to obtain a map of the second working area. After establishing the map of the second working area, the robot determines the first intersection point between the path and the second working area, i.e., intersection point 3, and moves to the position of intersection point 3 before continuing to move along the path. After reaching intersection point 4, the robot maps the first working area. Finally, after completing the mapping of the first working area, the robot moves to the position of intersection point 5 and then continues to move along the path until it reaches the charging station for charging, completing the mapping task of the three working areas.

[0116] It should also be noted that after the robot completes mapping of m work areas, it calculates the intersection points of each work area with the path, and extracts the path between these intersection points as a connecting path between two work areas. This connecting path is the path the user allows the robot to move outside the work area. The start and end points of the connecting path are located on the boundaries of different work areas. For example, in Figure 3, the path between intersection points 1 and 2 is used as the connecting path between the second and third work areas, and the path between intersection points 3 and 4 is used as the connecting path between the first and second work areas. When the starting point of the path is the location of the charging station and the charging station is outside the work area, the robot can also extract the path between the starting point and the second intersection point as the connecting path between the charging station and the work area. The second intersection point is the first intersection point between the robot and the first work area when the robot moves from the starting point to the end point of the path. For example, in Figure 2, the path between the charging station and intersection point 5 is used as the connecting path between the charging station and the work area.

[0117] As can be seen in this embodiment, firstly, the robot acquires a path, which passes through m working areas within the non-working area and the target area. Then, the robot moves along the acquired path. During the movement, if it is determined that the robot's position is in one of the working areas and that area has not yet been mapped, mapping is performed on that working area. If it is determined that the robot's position is in a non-working area, or if the robot's position is in a working area and that area has been mapped, the robot continues to move along the path. Compared to existing solutions where the user needs to participate in the entire mapping process until the mapping of m working areas is completed before leaving, in this solution, the user only needs to participate in the robot's path acquisition process; the subsequent mapping process is completed autonomously by the robot. This greatly reduces the user's waiting time and improves the user experience.

[0118] This application provides an apparatus for mapping a target area. Referring to Figure 4, Figure 4 is a structural schematic diagram of an apparatus 400 for mapping a target area provided in this application. The target area includes m working areas, where m is any positive integer greater than 1. The apparatus 400 includes:

[0119] The acquisition module 410 is used to acquire a path, wherein the path passes through m working areas in the non-working area and the target area;

[0120] The determination module 420 is used to determine if the robot's position is in one of the working areas and the working area has not been mapped, and to map the working area. If the robot's position is in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0121] In a possible implementation, module 410 is used for:

[0122] It receives instructions from the remote control device, responds to the instructions to move and collect multiple location points passed by the robot, and obtains the path based on the multiple location points.

[0123] In one possible implementation, the robot moves along a path from the end point of the path to the beginning point of the path, where the end point is the destination reached in response to the command, and the beginning point is the starting point of the movement in response to the command.

[0124] In one possible implementation, the starting point of the path is the location of the charging station, and the ending point of the path is any location within the last work area traversed by the path.

[0125] In possible implementations, the determining module 420 is used for:

[0126] During the movement, the robot acquires environmental information and determines its position within one of the work areas based on this information.

[0127] In a possible implementation, the determination module 420 is used to: identify the boundary of the work area based on environmental information, determine the intersection of the boundary and the path, and if the robot reaches the intersection, determine that the robot's position is located in one of the work areas.

[0128] In a possible implementation, the determination module 420 is used to: autonomously move within the work area to explore and map the work area when the robot's position is determined to be within one of the work areas and the work area has not been mapped.

[0129] In possible implementations, the determining module 420 is used for:

[0130] The first intersection point between the path and the work area is determined, and the robot moves to the position of the first intersection point. The first intersection point is the first intersection point in the work area that the robot passes through during its movement from the starting point of the path to the ending point of the path.

[0131] The robot continues to move along the path towards the starting point. During the movement, if the robot's position is determined to be in one of the working areas and the working area has not been mapped, the working area is mapped. If the robot's position is determined to be in a non-working area, or if the robot's position is in a working area and the working area has been mapped, the robot continues to move along the path.

[0132] Repeat the above steps until the robot moves to the starting point of the path.

[0133] In one possible implementation, the robot obtains the path from an external device, where the path is collected by the external device.

[0134] The various functional modules in Figure 4 are used to implement the steps of the method embodiments in Figures 1 to 3. For details, please refer to the description of the relevant content in the method embodiments in Figures 1 to 3. For the sake of brevity, they will not be repeated here.

[0135] This application also provides a computing device. Referring to Figure 5, Figure 5 is a schematic diagram of the structure of a computing device 500 provided in this application. The computing device 500 is used to implement the embodiments described in Figures 1 to 3. The computing device 500 can be a robot. The computing device 500 includes: a processor 510, a communication interface 520, and a memory 530. The processor 510, the communication interface 520, and the memory 530 can be interconnected through an internal bus 540, or they can communicate through wireless transmission or other means.

[0136] Taking a connection via bus 540 as an example, bus 540 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. Bus 540 can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in Figure 5, but this does not mean that there is only one bus or one type of bus.

[0137] Processor 510 may consist of at least one general-purpose processor, such as a CPU, or a combination of a CPU and hardware chips. The hardware chips may be application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or combinations thereof. The PLDs may be complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), generic array logic (GALs), or any combination thereof. Processor 510 executes various types of digital storage instructions, such as software or firmware programs stored in memory 530, enabling computing device 500 to provide a wide range of services.

[0138] The memory 530 is used to store program code and is controlled by the processor 510 to execute the steps described in the embodiments of Figures 1 to 3 above. For details, please refer to the relevant descriptions of the embodiments shown above, which will not be elaborated here.

[0139] The memory 530 may include volatile memory, such as RAM; the memory 530 may also include non-volatile memory, such as ROM or flash memory; the memory 530 may also include a combination of the above types.

[0140] The communication interface 520 can be a wired interface (e.g., an Ethernet interface), an internal interface (e.g., a high-speed serial computer expansion bus (PCIe) bus interface), a wired interface (e.g., an Ethernet interface), or a wireless interface (e.g., a cellular network interface or a wireless LAN interface), for communicating with other devices or modules.

[0141] The processor 510, communication interface 520, etc. in the computing device 500 can implement the functions and / or various steps and methods implemented in the above-described method embodiments, which will not be described in detail here for the sake of brevity. The acquisition module 410 and determination module 420 in the device 400 can be located in the processor 510 in the computing device 500.

[0142] It should be noted that Figure 5 is merely one possible implementation of an embodiment of this application. In practical applications, the computing device may include more or fewer components, which is not limited here. For content not shown or described in the embodiments of this application, please refer to the relevant descriptions in the foregoing method embodiments, which will not be repeated here.

[0143] This application also provides a computer storage medium including program instructions, which, when executed by a computing device, perform some or all of the steps described in the above embodiments of the method for mapping a target region.

[0144] This application also provides a computer program product, including program instructions that, when executed by a computing device, cause the computing device to perform some or all of the steps described in the above-described method embodiments for mapping a target region.

[0145] This application also provides a robot, including program instructions, which, when executed by the robot, cause the robot to perform some or all of the steps described in the above embodiments of the method for mapping a target region.

[0146] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0147] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, as a computer program product. The computer program product may contain code. When the computer program product is read and executed by a computer, some or all of the steps of the method described in the above method embodiments can be implemented. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium, or a semiconductor medium, etc.

[0148] The steps in the method of this application embodiment can be adjusted, merged, or deleted in order according to actual needs; the units in the device of this application embodiment can be divided, merged, or deleted according to actual needs.

[0149] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method of mapping a target area, characterized by, The target area includes m working areas, where m is any positive integer greater than 1. The method includes: The robot acquires a path, wherein the path passes through a non-working area and m working areas within the target area; The robot moves along the path. During the movement: if the robot's position is determined to be in one of the working areas and the working area has not been mapped, the working area is mapped; if the robot's position is determined to be in the non-working area, or if the robot's position is in the working area and the working area has been mapped, the robot continues to move along the path.

2. The method of claim 1, wherein, The robot acquisition path includes: The robot receives instructions from the remote control device, moves in response to the instructions, and collects multiple location points passed by the robot, thereby obtaining the path based on the multiple location points.

3. The method of claim 2, wherein, The robot's movement along the path includes: The robot moves along the path from the end point of the path to the beginning point of the path, where the end point of the path is the destination reached in response to the instruction, and the beginning point of the path is the starting point for movement in response to the instruction.

4. The method of claim 3, wherein, The starting point of the path is the location of the charging pile, and the ending point of the path is any location within the last work area traversed by the path.

5. The method according to any one of claims 1 to 4, characterized in that, During the movement, the robot acquires environmental information and determines its position within one of the work areas based on the environmental information.

6. The method of claim 5, wherein, Determining the robot's location within one of the work areas based on the environmental information includes: The robot identifies the boundary of the work area based on the environmental information, determines the intersection of the boundary and the path, and if the robot reaches the intersection, it is determined that the robot's position is located in one of the work areas.

7. The method according to any one of claims 1 to 4, characterized in that, When the robot's position is determined to be within a work area and the work area has not yet been mapped, mapping the work area includes: If the robot is located in one of the work areas and the work area has not been mapped, the robot can move autonomously within the work area to explore and map the work area.

8. The method of claim 3 or 4, wherein, When the robot's position is determined to be within a working area and the working area has not yet been mapped, after mapping the working area, the method further includes: The robot determines the first intersection point between the path and the work area, and moves to the position of the first intersection point, wherein the first intersection point is the first intersection point of the work area that the robot passes through during its movement from the starting point of the path to the ending point of the path; The robot continues to move along the path towards the starting point of the path. During the movement, if it is determined that the robot's position is in one of the working areas and the working area has not been mapped, the working area is mapped. If it is determined that the robot's position is in the non-working area, or if the robot's position is in the working area and the working area has been mapped, the robot continues to move along the path. Repeat the above steps until the robot moves to the starting point of the path.

9. The method of claim 1, wherein, The robot acquisition path includes: The robot obtains the path from an external device, wherein the path is collected by the external device.

10. The method of claim 1, wherein, The m work areas have no direct connection or overlap, and the robot moves from one work area through a non-work area to another work area.

11. The method of claim 2, wherein, The instructions include at least one of the following: move forward, move backward, move left, move right, stop, accelerate, and decelerate.

12. The method of claim 5, wherein, The environmental information includes visual information or lidar data.

13. The method of claim 1, wherein, The method further includes: after the robot completes the mapping of the m work areas, it calculates the intersection point of each work area with the path, and extracts the path between the intersection points from the path as a connecting path connecting the two work areas.

14. A computer storage medium, characterized in that Includes program instructions that, when executed by the robot, cause the robot to perform the method as described in any one of claims 1 to 13.

15. A robot, characterized in that Includes program instructions that, when executed by the robot, cause the robot to perform the method as described in any one of claims 1 to 13.

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