Control method, device, apparatus, medium and computer program of a self-moving device

Abstract

This application provides a control method, apparatus, device, storage medium, and computer program for a self-moving device, relating to the field of intelligent control technology. The method includes: acquiring regional height data of multiple location areas of a target obstacle during the movement of the self-moving device; and determining the height data of the target obstacle based on the regional height data of the multiple location areas, so as to control the self-moving device to pass over or bypass the target obstacle based on the height data. This application refines the data granularity and improves the data representation capability by using regional height data from multiple location areas, making the obstacle height data determined by the height data of each area more accurate, thereby improving the movement control capability of the self-moving device.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, and in particular to a control method, apparatus, device, storage medium, and computer program for a self-moving device. Background Technology

[0002] For self-moving devices such as robotic vacuum cleaners and agricultural robots to operate safely in complex environments, the key lies in accurately identifying surrounding obstacles and overcoming obstacles within a certain height range. While obstacle recognition technology is constantly improving with the development of artificial intelligence and sensor technology, it still faces many challenges.

[0003] In related technologies, taking robotic vacuum cleaners as an example, when an obstacle is detected as a threshold, it is necessary to accurately identify thresholds of different heights in order to control the robotic vacuum cleaner to perform corresponding actions, such as crossing the threshold or going around it. Therefore, it is necessary to provide a method that can accurately identify threshold heights. Summary of the Invention

[0004] This application provides a control method, apparatus, device, storage medium, and computer program for a self-moving device, which solves the problem of inaccurate identification of obstacle height in the prior art.

[0005] According to one aspect of this application, a control method for a self-moving device is provided, the method comprising: During the movement of the self-moving device, acquire regional height data of multiple location areas of the target obstacle; Based on regional height data from multiple location areas, determine the height data of the target obstacle; Based on altitude data, control the autonomous mobile device to cross or bypass target obstacles.

[0006] In one possible implementation, the aforementioned self-moving device includes a device body on which a spatial information sensor is disposed; The above-mentioned acquisition of regional height data for multiple location areas of the target obstacle includes: Acquire real-time spatial information of target obstacles collected by spatial information sensors; Based on real-time spatial information, determine the regional height data of multiple location areas of the target obstacle.

[0007] In yet another possible implementation, the aforementioned area height data includes height values; The above-mentioned regional height data, based on multiple location areas, determines the height data of the target obstacle, including: Determine the region height type based on the height value; Clustering is performed on each location region based on its height type to obtain the height data of the target obstacle.

[0008] In yet another possible implementation, the aforementioned region height types include the first type, the second type, and the third type; The above-mentioned region height types, which determine the corresponding location area based on height values, include: If the height value of the location area is greater than the first height threshold and not greater than the second height threshold, then the area height type of the corresponding location area is determined to be the first type. If the height value of the location area is greater than the second height threshold but not greater than the third height threshold, then the area height type of the corresponding location area is determined to be the second type. If the height value of the location area is greater than the third height threshold, then the area height type of the corresponding location area is determined to be the third type; wherein, the first height threshold is less than the second height threshold, and the second height threshold is less than the third height threshold.

[0009] In another possible implementation, the above-mentioned clustering of each location region based on region height type yields the height data of the target obstacle, including: For each first position region corresponding to the first type and each second position region corresponding to the second type, a first polygon is generated; wherein the first polygon covers all first position regions and second position regions, and the area of ​​the first polygon is not greater than a preset first threshold. For each second location region corresponding to the second type, a second polygon is generated; wherein the second polygon covers all second location regions, and the area of ​​the second polygon is less than a preset second threshold. The height data of the target obstacle is determined based on the first polygon and the second polygon.

[0010] In another possible implementation, the determination of the target obstacle's height data based on the first and second polygons includes: If the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the target obstacle is determined to be the first single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the target obstacle is determined to be the second single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the step depth is determined based on the positional relationship between the first polygon and the second polygon. The height data of the target obstacle is determined based on the step depth.

[0011] In one possible implementation, each location region is a rectangular region, and both the first polygon and the second polygon mentioned above are rectangles. The above determination of the step depth based on the positional relationship between the first polygon and the second polygon includes: Determine the target location of the mobile device at the moment of real-time spatial information acquisition; Determine the first target edge in the first polygon that is on the same side as the target position, and the second target edge in the second polygon that is on the same side as the target position; The horizontal distance between the first target edge and the second target edge is taken as the step depth.

[0012] In one possible implementation, the above-mentioned data for determining the height of the target obstacle based on the step depth includes: If the step depth is greater than the target depth threshold, the height data is determined to be of the first double-layer type; Otherwise, determine the height data as the second double-layer type.

[0013] In yet another possible implementation, the above clustering conditions include: The first side of the target polygon is longer than a preset length threshold, and the second side of the target polygon is longer than a preset width threshold; wherein, the target polygon is either a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon that is on the same side as the target position, and the second side length is the side length of the second side of the target polygon that is adjacent to the first side.

[0014] In yet another possible implementation, the aforementioned self-moving device also includes an obstacle-crossing assist device; The above-mentioned methods for controlling a self-moving device to cross or bypass target obstacles based on altitude data include: Based on altitude data, the self-moving device is controlled to cross or bypass target obstacles, and the working state of the obstacle crossing assistance device is controlled during the movement; the working state is either the obstacle crossing assistance state or the storage state.

[0015] In another possible implementation, the above-mentioned control of the self-moving device to cross or bypass the target obstacle based on altitude data, and control of the working state of the obstacle-crossing assistance device during movement, includes: If the height data is of the first single-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to the storage state during the movement; If the height data is of the second single-layer type or the second double-layer type, control the self-moving device to bypass the target obstacle, and control the obstacle-crossing assist device to be in the storage state during the movement. If the height data is of the first double-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to the obstacle crossing assist state during the movement.

[0016] In another possible implementation, the aforementioned target obstacle includes a threshold; The above-mentioned acquisition of regional height data for multiple location areas of the target obstacle includes: Image data acquired from the mobile device in the pre-movement direction; If a threshold is identified based on image data, then the regional height data of multiple location areas of the threshold is obtained.

[0017] According to another aspect of the embodiments of this application, a control device for a self-moving device is provided, the device comprising: The acquisition module is used to acquire regional height data of multiple location areas of the target obstacle during the movement of the self-moving device; and to determine the height data of the target obstacle based on the regional height data of multiple location areas. The control module is used to control the self-moving device to cross or bypass target obstacles based on altitude data.

[0018] According to another aspect of this application, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method shown in the first aspect of this application.

[0019] According to another aspect of this application, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause a computer to perform the steps of the method shown in the first aspect of this application.

[0020] According to another aspect of this application, a computer program product is provided, the computer program product including instructions that, when executed, cause a computer to perform the steps of the method shown in the first aspect of this application.

[0021] The beneficial effects of the technical solution provided in this application are: The self-moving device control method provided in this application can acquire regional height data of multiple location areas of a target obstacle during the movement of the self-moving device, and determine the height data of the target obstacle based on the height data of each region; during the movement of the self-moving device, it can control the self-moving device to cross or avoid the target obstacle based on the height data; this application refines the data granularity and improves the data representation capability by using regional height data of multiple location areas, making the obstacle height data determined by the height data of each region more accurate, thereby improving the movement control capability of the self-moving device; at the same time, this application can also greatly reduce the obstacle crossing failure rate of the self-moving device, further improving the work efficiency. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating a control method for a self-moving device provided in an embodiment of this application; Figure 2 A schematic diagram of a scenario for spatial sensing data detection in a control method for a self-moving device provided in an embodiment of this application; Figure 3 A top-down view of a scene for target obstacle height recognition in a control method for a self-moving device provided in this application embodiment; Figure 4 This is a schematic diagram of a clustering scenario of a location region in a control method for a self-moving device provided in an embodiment of this application; Figure 5 This is a schematic diagram of a clustering scenario for another location region in a control method for a self-moving device provided in an embodiment of this application; Figure 6 This is a schematic diagram illustrating a clustering scenario of another location region in a control method for a self-moving device provided in an embodiment of this application. Figure 7 A schematic diagram illustrating a scenario for determining the depth of a step in a control method for a self-moving device provided in an embodiment of this application; Figure 8 A flowchart illustrating an example of a self-moving device control method provided in an embodiment of this application; Figure 9 A schematic diagram of the structure of a control device for a self-moving device provided in an embodiment of this application; Figure 10This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] Embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0025] The accompanying drawings illustrate various structural schematics according to embodiments of the present disclosure. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0026] In the context of this disclosure, when a layer / element is referred to as being "above" another layer / element, the layer / element may be directly above the other layer / element, or there may be an intermediate layer / element between them. Additionally, if a layer / element is "above" another layer / element in one orientation, then when the orientation is reversed, the layer / element may be "below" the other layer / element.

[0027] The core of the development of autonomous mobile devices lies in the continuous optimization of the "perception-decision-execution" closed loop. The evolution of obstacle avoidance, path planning and intelligent algorithms has jointly promoted the autonomy and adaptability of devices in complex environments.

[0028] The synergistic evolution of sensor fusion and intelligent algorithms is a key driving force for the development of self-moving devices. Sensors provide the "eyes" for environmental perception, while intelligent algorithms act as the "brain." For example, multimodal fusion technology combines the spatial information of vision, the 3D accuracy of Light Laser Detection and Ranging (LiDAR), and the ranging capabilities of radar to achieve a comprehensive understanding of the environment. Simultaneously, the development of algorithms such as deep learning enables devices to learn from massive amounts of data and optimize obstacle avoidance and path planning strategies, achieving a shift from "rule-driven" to "data-driven" approaches.

[0029] Self-moving devices have diverse application scenarios, ranging from urban roads and farmland to indoor environments, with vastly different environmental complexities and obstacle types. Accurately identifying obstacle heights in different scenarios to improve the obstacle-crossing capabilities of self-moving devices is of great significance for promoting their widespread application.

[0030] Based on the aforementioned technical problems, some embodiments of this application can acquire regional height data of multiple location areas of a target obstacle during the movement of the self-moving device, and determine the height data of the target obstacle based on the height data of each region; during the movement of the self-moving device, it can control the self-moving device to cross or avoid the target obstacle based on the height data; this application refines the data granularity and improves the data representation capability by using regional height data of multiple location areas, making the obstacle height data determined by the height data of each region more accurate, thereby improving the movement control capability of the self-moving device; at the same time, this application can also greatly reduce the obstacle crossing failure rate of the self-moving device, further improving the work efficiency.

[0031] The technical solutions of this application and how they solve the aforementioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0032] This application provides a method for controlling a self-moving device, such as... Figure 1 As shown, this method, which can be applied to self-moving devices, may include: S101: During the movement of the self-moving device, acquire regional height data of multiple location areas of the target obstacle.

[0033] The aforementioned regional altitude data is used to characterize spatial altitude information within the location area; this regional altitude data can be obtained based on spatial information sensors installed on the main body of the mobile device. The aforementioned spatial information sensors may include at least one, and may include a Time of Flight (TOF) sensor, a visual sensor, and a Laser Distance Sensor (LDS).

[0034] Specifically, during the movement of the self-moving device, multiple frames of real-time spatial information of the target obstacle are collected based on spatial information sensors, and regional height data of multiple location areas are determined based on the multiple frames of real-time spatial information.

[0035] In this embodiment of the application, taking a robotic vacuum cleaner as an example, when performing mapping or cleaning tasks, the spatial information of the target obstacle can be collected by a spatial information sensor during the movement process, and the regional height data of multiple location areas corresponding to the target obstacle can be determined based on the spatial information.

[0036] In some implementations, if the self-moving device is a lawnmower, the corresponding target obstacle can be a staircase.

[0037] In other implementations, if the self-moving device is a robotic vacuum cleaner, the corresponding target obstacle can be a threshold.

[0038] S102, determine the height data of the target obstacle based on the regional height data of multiple location areas.

[0039] The height data of the target obstacle can include the height value and height type. Taking a robotic vacuum cleaner as the self-moving device and a threshold as the target obstacle as an example, the height data can include the threshold's level, as well as the height and depth values ​​of each level.

[0040] Optionally, after determining the height data of the target obstacle, the height data can be saved to a map of the target area so that when the self-moving device performs operations in the target area, it can directly obtain the height data of the target obstacle from the map to control the movement of the self-moving device based on the height data.

[0041] Furthermore, after determining the height data of the target obstacle, the process may also include: Obtain the map height data of the target obstacle from the preset map. If the height data is inconsistent with the map height data, update the preset map based on the height data to ensure the timeliness and accuracy of the height data in the map.

[0042] At the same time, based on a preset recognition frequency, such as every 30 days, the self-moving device in operation can be controlled to recognize the height data of the target obstacle in real time, so as to update the preset map in real time when the recognition data is inconsistent with the map data.

[0043] S103 controls the self-moving device to cross or bypass target obstacles based on altitude data.

[0044] The aforementioned height data may include the height value and height type of the target obstacle.

[0045] In some implementations, if the self-moving device determines that it can overcome the target obstacle based on the height value and height type, then different obstacle-crossing actions can be determined based on the height value and height type to complete the obstacle crossing. In other implementations, if the self-moving device determines, based on the height value and height type, that it cannot overcome the target obstacle, it can detour to avoid the obstacle.

[0046] Specifically, taking a robotic vacuum cleaner as the self-moving device and a threshold as the target obstacle, the robotic vacuum cleaner can collect spatial information about the threshold using spatial information sensors during its movement, and determine the threshold's height based on this information. If the height data determines that the robotic vacuum cleaner can overcome the threshold, it can then cross the threshold after mapping or cleaning is complete and perform pre-set operations on the area behind the threshold.

[0047] This application embodiment can acquire regional height data of multiple location areas of a target obstacle during the movement of the self-moving device, and determine the height data of the target obstacle based on the height data of each region; during the movement of the self-moving device, it can control the self-moving device to cross or avoid the target obstacle based on the height data; this application refines the data granularity and improves the data representation capability by using regional height data of multiple location areas, making the obstacle height data determined by the height data of each region more accurate, thereby improving the movement control capability of the self-moving device; at the same time, this application can also greatly reduce the obstacle crossing failure rate of the self-moving device, further improving the work efficiency.

[0048] This application provides a possible implementation method in which the self-moving device includes a device body and a spatial information sensor is provided on the device body.

[0049] Optionally, the sidewalls of the main body of the device may be equipped with spatial sensors along the direction of movement. These spatial sensors may include at least one, and may include Time-of-Flight (TOF), vision sensors, and LDS sensors, etc.

[0050] The above-mentioned acquisition of regional height data for multiple location areas of the target obstacle includes: S201, acquire real-time spatial information of the target obstacle collected by the spatial information sensor.

[0051] Wherein, if the aforementioned spatial information sensor is a Time-of-Flight (TOF) sensor, the corresponding real-time spatial information can be a depth map; if the aforementioned spatial information sensor is an LDS sensor, the aforementioned real-time spatial information can be point cloud data; if the aforementioned spatial information sensor is a vision sensor, the aforementioned real-time spatial information can be image data.

[0052] S202, determine the regional height data of multiple location areas of the target obstacle based on real-time spatial information.

[0053] The moving surface of the self-moving device may include multiple adjacent, non-overlapping region units; the aforementioned location regions may be determined based on the region units corresponding to the projection of the target obstacle onto the moving surface. Each location region may correspond to at least one region unit.

[0054] Specifically, real-time spatial information can be partitioned based on location regions to determine the regional height data of multiple location regions of the target obstacle. The specific method for determining the regional height data of multiple location regions will be explained in detail below.

[0055] This application embodiment uses real-time spatial information of target obstacles collected by spatial information sensors to determine the regional height data of multiple location areas of target obstacles based on real-time spatial information, ensuring real-time identification of height data, further improving the perception and adaptability of the self-moving device to the working environment, and improving the working efficiency of the self-moving device.

[0056] This application provides a possible implementation method in which the real-time spatial information includes multiple real-time spatial sub-information; each real-time spatial sub-information corresponds to a target region unit, and each target region unit covers the projection of the corresponding real-time spatial sub-information onto the moving surface.

[0057] The aforementioned regional height data for determining multiple location areas of the target obstacle based on real-time spatial information includes: S301, determine the cell height data of the corresponding target area cell based on each real-time spatial sub-information.

[0058] Specifically, taking a spatial information sensor as an LDS and real-time spatial information as point cloud data as an example, if a target obstacle is detected, the point cloud data corresponding to the target obstacle can be collected, and the point cloud data can be divided into multiple point cloud sub-data based on regional units; and the height value of the highest point in each point cloud sub-data can be used as the unit height data of the corresponding target regional unit.

[0059] like Figure 2 As shown, taking the robotic vacuum cleaner 20 as an example, its main body 202 is equipped with an LDS sensor 201 on its side wall. The LDS sensor 201 emits a vertical laser and generates point cloud data 203 distributed on the surface of the target obstacle 204.

[0060] Optionally, such as Figure 3 The diagram shows a top-down view of a target obstacle recognition scenario. The moving plane can be pre-divided into multiple region units 301, for example, each region unit can be a 5cm*5cm square. Then, based on the region units, the point cloud data 203 is divided into multiple point cloud sub-data. Each point cloud sub-data corresponds to a target region unit 302, where a target region unit 302 can completely cover the projection of the corresponding point cloud sub-data onto the moving surface.

[0061] S302, the cell height data of each target area cell on the moving surface is used as the area height data of the corresponding target obstacle's location area.

[0062] Among them, multiple location regions can be the projection areas of target obstacles on the moving surface, and each target region unit corresponds to a location region.

[0063] In this embodiment, since the spatial information sensor detects based on a preset frequency as the mobile device moves, the projection of the collected real-time spatial information onto the moving plane is discontinuous. In order to obtain accurate height data, the height data of each region can be used to cluster the various locations of the target obstacle to obtain the height data of the target obstacle, thereby ensuring the accuracy of the height data of the target obstacle. The specific process of determining the height data of the target obstacle will be described in detail below.

[0064] This application provides a possible implementation method, wherein the above-mentioned area height data includes height values.

[0065] Taking LDS as the spatial information sensor and point cloud data as the real-time spatial information as an example, the point cloud data can be divided into multiple point cloud sub-data based on regional units. In some embodiments, the height value of the highest point in each point cloud sub-data can be used as the height value of the corresponding target regional unit. In other embodiments, the average height of all points in each point cloud sub-data can be used as the height value of the corresponding target regional unit. No specific limitation is made in this application.

[0066] The above-mentioned regional height data, based on multiple location areas, determines the height data of the target obstacle, including: S401, determine the region height type of the corresponding location area based on the height value.

[0067] Specifically, this application provides a possible implementation method, wherein the above-mentioned region height type includes a first type, a second type, and a third type.

[0068] The process of determining the height type of the aforementioned area may include: If the height value of the location area is greater than the first height threshold and not greater than the second height threshold, then the area height type of the corresponding location area is determined to be the first type. If the height value of the location area is greater than the second height threshold but not greater than the third height threshold, then the area height type of the corresponding location area is determined to be the second type. If the height value of the location area is greater than the third height threshold, then the area height type of the corresponding location area is determined to be the third type.

[0069] Among them, the first altitude threshold is less than the second altitude threshold, and the second altitude threshold is less than the third altitude threshold.

[0070] Furthermore, taking the self-moving device as a robotic vacuum cleaner and the target obstacle as a threshold as an example; the first height threshold can be 2.5cm, which is the minimum threshold height at which the robotic vacuum cleaner needs to perform obstacle-crossing actions; the second height threshold can be 4.5cm, which is the highest single-layer threshold height at which the robotic vacuum cleaner can complete obstacle crossing; the third height threshold can be 8.5cm, which is the highest height at which the robotic vacuum cleaner can complete obstacle crossing of two layers of thresholds.

[0071] S402, clustering of each location region based on the region height type to obtain the height data of the target obstacle.

[0072] Specifically, the height data of the target obstacle can be obtained by clustering the location regions based on their positional relationships and height types. The specific process for determining the height data will be explained in detail below.

[0073] This application embodiment refines the granularity of height data processing by dividing real-time spatial information into multiple real-time spatial sub-information, effectively ensuring the precision of regional height data. At the same time, it can perform clustering processing on each location region based on the positional relationship between each location region and the region height type, realizing the aggregation of data granularity from small to large, further improving the accuracy of target obstacle height data, and laying a good foundation for the subsequent mobile control of self-moving devices.

[0074] This application provides a possible implementation method in which the above-mentioned clustering of each location region based on the region height type is performed to obtain the height data of the target obstacle, including: S501, Generate a first polygon for each first position region corresponding to the first type and each second position region corresponding to the second type.

[0075] The first polygon covers all first and second location regions, and the area of ​​the first polygon is not greater than a preset first threshold.

[0076] Specifically, multiple first candidate polygons can be determined based on the positions of each first and second position regions, and then the first polygon with the smallest area can be selected from the multiple first candidate polygons.

[0077] The first threshold mentioned above can be determined based on the area of ​​the first candidate polygon with the smallest area.

[0078] Optionally, such as Figure 4As shown, taking a 5cm*5cm square for each position area and a rectangle for the first polygon as an example, all rectangles that can cover the entire first position area 401 and second position area 402 can be traversed based on the center point of each first position area 401 and second position area 402 and the side length of the position area until the area of ​​the rectangle is the smallest. The rectangle with the smallest area is then taken as the first polygon 403 mentioned above.

[0079] S502, Generate a second polygon for each second position region corresponding to the second type.

[0080] The second polygon covers all the second location regions, and the area of ​​the second polygon is less than a preset second threshold.

[0081] Specifically, multiple candidate polygons can be determined based on the location of each second target area, and then the second polygon with the smallest area can be selected from the multiple candidate polygons.

[0082] The second threshold can be determined based on the area of ​​the second candidate polygon with the smallest area.

[0083] Optionally, such as Figure 4 As shown, taking a 5cm*5cm square for each position area and a rectangle for the second polygon as an example, all rectangles that can cover the entire second position area 402 can be traversed based on the center point of each second position area 402 and the side length of the position area until the area of ​​the rectangle is the smallest. The rectangle with the smallest area is then used as the second polygon 404 mentioned above.

[0084] S503, determine the height data of the target obstacle based on the first polygon and the second polygon.

[0085] Specifically, the height data of the target obstacle can be determined based on the positional relationship between the first polygon and the second polygon.

[0086] This application embodiment generates a first polygon by generating each first location region corresponding to the first type and each second location region corresponding to the second type; and generates a second polygon for each second location region corresponding to the second type; thus realizing the clustering of each location region. The height type and height value of the target obstacle can be determined by the first polygon and the second polygon to achieve accurate height identification. The specific method for determining the height data will be described in detail below.

[0087] This application provides a possible implementation method where each location region is a rectangular region. The height data of the target obstacle determined based on the first polygon and the second polygon includes: In some implementations, if the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the target obstacle is determined to be the first single-layer type.

[0088] The clustering conditions can be determined based on the side length of the first or second polygon, as well as the size of the self-moving device's main body.

[0089] Specifically, such as Figure 5 As shown, if the side length of the first polygon 501 satisfies the preset clustering condition, but the side length of the second polygon does not satisfy the preset clustering condition, it can be characterized that in the projection of the target obstacle on the moving surface, there is a first position region 502 of the first type and no second position region of the second type. It can be determined that the height value of the target obstacle is between the first height threshold and the second height threshold, and is a low single-layer structure.

[0090] In other implementations, if the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the target obstacle is determined to be the second single-layer type.

[0091] Specifically, such as Figure 6 As shown, if the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, but the areas of the first polygon and the second polygon are the same, then it indicates that the first polygon 601 and the second polygon 602 overlap. In the projection of the target obstacle onto the moving surface, there is a second position region 603 of the second type and no first position region of the first type. Then it can be determined that the height value of the target obstacle is between the second height threshold and the third height threshold, which is a relatively high single-layer structure.

[0092] In some other implementations, if the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the step depth is determined based on the positional relationship between the first polygon and the second polygon; and the height data of the target obstacle is determined based on the step depth.

[0093] Specifically, if the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then it indicates that there is an intersection area between the first polygon and the second polygon, and the target obstacle is a double-layered staircase shape. The height and depth information of each layer can be determined based on the shape of the first polygon and the second polygon. The steps for determining the specific shape and size of the double-layered staircase will be explained in detail below.

[0094] This application provides a possible implementation method, wherein the above clustering conditions include: The first side of the target polygon is longer than a preset length threshold, and the second side of the target polygon is longer than a preset width threshold.

[0095] The target polygon is either a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon that is on the same side as the target position, and the second side length is the side length of the second side of the target polygon that is adjacent to the first side.

[0096] Furthermore, the aforementioned target location refers to the target location of the mobile device at the moment of real-time spatial information acquisition.

[0097] Specifically, the aforementioned length and width thresholds can be determined based on the main body of the self-moving device; taking a robotic vacuum cleaner as an example, the length threshold can be the diameter of the robot, such as 34cm; the width threshold can be determined based on the width required for the robotic vacuum cleaner to overcome obstacles, such as 10cm.

[0098] This application embodiment determines the height data of a target obstacle by the positional relationship between a first polygon and a second polygon. If the first polygon clusters successfully but the second polygon fails to cluster, the height value of the target obstacle can be determined to be between a first height threshold and a second height threshold, indicating a low, single-layer structure. If both the first and second polygons cluster successfully and overlap, the height value of the target obstacle can be determined to be between a second height threshold and a third height threshold, indicating a higher, single-layer structure. If both the first and second polygons cluster successfully and there is an intersection between them, the height and step depth information of each level can be determined based on the shapes of the first and second polygons. This application embodiment achieves the classification of multi-layer steps and multi-layer step structures, enabling accurate multi-level identification of the height of the target obstacle based on its height type, further improving the accuracy of subsequent self-moving device control.

[0099] This application provides a possible implementation method in which the first polygon and the second polygon can both be rectangles.

[0100] The above determination of the step depth based on the positional relationship between the first polygon and the second polygon includes: S601, determine the target location of the self-moving device at the moment of real-time spatial information acquisition.

[0101] like Figure 7 As shown, taking a self-moving device as a robotic vacuum cleaner as an example, at the moment of real-time spatial information collection, the center point of the robotic vacuum cleaner, i.e. the target position A, is located on one side of the target obstacle 70.

[0102] S602, determine the first target edge in the first polygon that is on the same side as the target position, and the second target edge in the second polygon that is on the same side as the target position; take the horizontal distance between the first target edge and the second target edge as the step depth.

[0103] like Figure 7 As shown, the first target edge 703 in the first polygon 701 and the second target edge 704 in the second polygon 702 can be determined. The horizontal distance between the first target edge 703 and the second target edge 704 is used as the step depth D.

[0104] In this embodiment of the application, by determining the target position of the self-moving device, the first target edge in the first polygon and the second target edge in the second polygon are determined, thereby realizing the identification of the step depth. Based on the first polygon and the second polygon, the boundary of the target obstacle is effectively characterized, which further improves the accuracy of the step depth and lays a good foundation for the subsequent movement control of the self-moving device.

[0105] This application provides a possible implementation method, in which the above-mentioned determination of the height data of the target obstacle based on the step depth includes: If the step depth is greater than the target depth threshold, the height data is determined to be of the first double-layer type; Otherwise, determine the height data as the second double-layer type.

[0106] The target depth threshold can be determined based on the main body of the self-moving device; taking a robotic vacuum cleaner as an example, the target depth threshold can be determined based on the width required for the robotic vacuum cleaner to overcome obstacles, such as 10cm.

[0107] In this embodiment, if the target obstacle is a two-layer structure, the step depth information can be determined by the intersection area of ​​the first polygon and the second polygon, and the height type can be determined based on the step depth. If the step depth is greater than the target depth threshold, it can be determined that the step depth is sufficient to provide enough space for the self-moving device to overcome the obstacle, that is, the first two-layer type is the height type that the self-moving device can overcome. If the step depth is not greater than the target depth threshold, it can be determined that the step depth cannot provide enough space for the self-moving device to overcome the obstacle, that is, the second two-layer type is the height type that the self-moving device cannot overcome. This achieves accurate identification of two-layer obstacles.

[0108] This application provides a possible implementation method, in which the self-moving device further includes an obstacle-crossing assistance device.

[0109] For example, the aforementioned obstacle-crossing assist device can be a swing arm wheel or a robotic arm.

[0110] The above-mentioned methods for controlling a self-moving device to cross or bypass target obstacles based on altitude data include: Based on altitude data, the self-moving device is controlled to cross or bypass target obstacles, and the working status of the obstacle crossing assistance device is controlled during the movement.

[0111] The working states are either obstacle-crossing assistance or storage.

[0112] Specifically, the aforementioned height data can represent height type and height value; it can determine whether the self-moving device can complete the obstacle crossing operation for the target obstacle based on the height type; and when the obstacle crossing operation can be completed, different obstacle crossing actions can be determined based on different height values, further improving the precision of obstacle crossing movement control of the self-moving device and increasing the obstacle crossing success rate.

[0113] This application provides a possible implementation method in which the above-mentioned self-moving device is controlled to cross or bypass target obstacles based on altitude data, and the working state of the obstacle-crossing assistance device is controlled during the movement, including: In some implementations, if the height data is of the first single-layer type, the self-moving device is controlled to cross the target obstacle, and the obstacle crossing assist device is controlled to be in a stowage state during the movement.

[0114] Specifically, if the height data is of the first single-layer type, it indicates that the self-moving device can complete obstacle crossing on its own, and can be controlled to directly cross the target obstacle, while the obstacle crossing assist device remains in a retracted state during the movement.

[0115] In other embodiments, if the height data is a second single-layer type or a second double-layer type, the self-moving device is controlled to bypass the target obstacle, and the obstacle-crossing assist device is controlled to be in a stowage state during the movement.

[0116] Specifically, if the height data is of the second single-layer type or the second double-layer type, it indicates that the self-moving device cannot complete the obstacle crossing even with the assistance of the obstacle crossing assist device. It can control the self-moving device to bypass the target obstacle and keep the obstacle crossing assist device in a retracted state during the movement.

[0117] In some other implementations, if the height data is of the first dual-layer type, the self-moving device is controlled to cross the target obstacle, and during the movement, the working state of the obstacle crossing assist device is controlled to be the obstacle crossing assist state.

[0118] Specifically, if the height data is of the first double-layer type, it indicates that the self-moving device can complete obstacle crossing with the assistance of the obstacle crossing assist device. It can control the self-moving device to cross the target obstacle and control the obstacle crossing assist device to maintain its working state during the movement. At the same time, it can also determine the obstacle crossing action of the obstacle crossing assist device based on different height values ​​to ensure the success rate of obstacle crossing.

[0119] This application provides a possible implementation method, wherein the target obstacle includes a threshold; The above-mentioned acquisition of regional height data for multiple location areas of the target obstacle includes: S701, image data acquired from the mobile device in the pre-movement direction.

[0120] Optionally, an image acquisition device may also be installed on the main body of the self-moving device.

[0121] Specifically, the self-moving device can acquire image data in the direction of the intended movement through an image acquisition device during the movement process.

[0122] S702, if a threshold is identified based on image data, then obtain the regional height data of multiple location areas of the threshold.

[0123] Specifically, image data can be identified using an image recognition model. If a threshold is identified, a spatial information sensor is triggered to collect real-time spatial information of the threshold, and the threshold's height is determined based on this real-time spatial information. The specific method for determining the height data can refer to the steps for determining the height data of the target obstacle described above, and will not be repeated here.

[0124] This application embodiment identifies thresholds within a moving plane by acquiring image data. When a threshold is identified based on the image data, a spatial information sensor detects the precise height data of the threshold to determine whether it is necessary to cross the threshold and perform operations on the area behind the threshold. Simultaneously, when it is possible to cross the threshold, different obstacle-crossing actions are determined based on the height data to ensure the success rate of threshold crossing and further improve the user experience.

[0125] To better understand the control method of the self-moving device described above, the following will combine... Figure 8 This paper details an example of a control method for a self-moving device according to this application, applied to a robotic vacuum cleaner. The method includes the following steps: The S801 can collect image data of the pre-movement direction in real time during the process of the robot vacuum cleaning room A.

[0126] S802: If a threshold is identified based on image data, then real-time point cloud data for the threshold is collected via LDS.

[0127] S803 can pre-divide the movable plane in room A into multiple 5cm*5cm area units, and then divide the point cloud data into multiple point cloud sub-data based on the area units.

[0128] Each point cloud sub-data corresponds to a target region unit, and a target region unit can completely cover the projection of the corresponding point cloud sub-data onto the moving surface.

[0129] S804 uses the height value of the highest point in each cloud sub-data as the cell height data of the corresponding target area cell.

[0130] S805, determine the cell height type of the corresponding target area cell based on the height value.

[0131] Specifically, if the height value of the target area unit is greater than 2.5cm and not greater than 4.5cm, then the unit height type of the corresponding target area unit is determined to be the first type; If the height value of the target area unit is greater than 4.5cm and not greater than 8.5cm, then the unit height type of the corresponding target area unit is determined to be the second type; If the height value of the target area unit is greater than 8.5cm, then the unit height type of the corresponding target area unit is determined to be the third type.

[0132] S806, for each first target region unit corresponding to the first type and each second target region unit corresponding to the second type, generate a first polygon that covers all first target region units and has the smallest area; for each second target region unit corresponding to the second type, generate a second polygon that covers all second target region units and has the smallest area.

[0133] S807, if the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the threshold is determined to be the first single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the threshold is determined to be the second single-layer type.

[0134] Simultaneously, if the side lengths of both the first and second polygons satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the first target edge on the same side as the target position in the first polygon and the second target edge on the same side as the target position in the second polygon are determined respectively; the horizontal distance between the first target edge and the second target edge is taken as the step depth. If the step depth is greater than 10cm, the height data is determined to be of the first double-layer type; otherwise, the height data is determined to be of the second double-layer type.

[0135] The clustering conditions mentioned above include: The first side of the target polygon is longer than 34cm, and the second side of the target polygon is longer than 10cm.

[0136] Wherein, the target polygon is either a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon on the same side as the target position, and the second side length is the side length of the second side of the target polygon adjacent to the first side. Further, the aforementioned target position is the target position of the sweeping robot at the moment of real-time spatial information acquisition.

[0137] S808, after completing the cleaning of room A, determines based on height data whether it is necessary to cross the threshold to clean the area of ​​room B behind the threshold.

[0138] If the height data is of the first single-layer type, it indicates that the robot vacuum can overcome obstacles on its own. It can be controlled to directly overcome obstacles such as thresholds, and the swing arm wheels remain in a retracted state during the movement.

[0139] If the height data is of the second single-layer type or the second double-layer type, it indicates that the robot vacuum cleaner cannot overcome obstacles even with the assistance of the swing arm wheel. It can control the robot vacuum cleaner to avoid the threshold and keep the swing arm wheel in the storage state during the movement.

[0140] Specifically, if the height data is of the first double-layer type, it indicates that the robot vacuum can overcome obstacles with the assistance of the swing arm wheel. It can control the robot vacuum to cross the threshold and keep the swing arm wheel in working state during the movement. At the same time, it can determine the obstacle-crossing action of the swing arm wheel based on different height values ​​to ensure the success rate of obstacle crossing.

[0141] This application provides a control device for a self-moving device, such as... Figure 9 As shown, the control device 90 of the self-moving device may include: an acquisition module 901 and a control module 902; The acquisition module 901 is used to acquire regional height data of multiple location areas of the target obstacle during the movement of the self-moving device; and to determine the height data of the target obstacle based on the regional height data of the multiple location areas. The control module 902 is used to control the self-moving device to cross or bypass the target obstacle based on altitude data.

[0142] This application provides a possible implementation method, wherein the self-moving device includes a device body and a spatial information sensor is provided on the device body; When acquiring the area height data of multiple location regions of the target obstacle, the aforementioned acquisition module 901 is used for: Acquire real-time spatial information of target obstacles collected by spatial information sensors; Based on real-time spatial information, determine the regional height data of multiple location areas of the target obstacle.

[0143] This application provides a possible implementation method, wherein the above-mentioned area height data includes height values; When determining the height data of a target obstacle based on regional height data from multiple location areas, the aforementioned acquisition module 901 is used for: Determine the region height type based on the height value; Clustering is performed on each location region based on its height type to obtain the height data of the target obstacle.

[0144] This application provides a possible implementation method, wherein the height type includes a first type, a second type, and a third type; When determining the region height type of the corresponding location area based on the height value, the aforementioned acquisition module 901 is used for: If the height value of the location area is greater than the first height threshold and not greater than the second height threshold, then the area height type of the corresponding location area is determined to be the first type. If the height value of the location area is greater than the second height threshold but not greater than the third height threshold, then the area height type of the corresponding location area is determined to be the second type. If the height value of the location area is greater than the third height threshold, then the area height type of the corresponding location area is determined to be the third type; wherein, the first height threshold is less than the second height threshold, and the second height threshold is less than the third height threshold.

[0145] This application embodiment provides a possible implementation method in which the acquisition module 901, when performing clustering processing on each location region based on the region height type to obtain the height data of the target obstacle, is used to: For each first position region corresponding to the first type and each second position region corresponding to the second type, a first polygon is generated; wherein the first polygon covers all first position regions and second position regions, and the area of ​​the first polygon is not greater than a preset first threshold. For each second location region corresponding to the second type, a second polygon is generated; wherein the second polygon covers all second location regions, and the area of ​​the second polygon is less than a preset second threshold. The height data of the target obstacle is determined based on the first polygon and the second polygon.

[0146] This application embodiment provides a possible implementation method in which the acquisition module 901, when determining the height data of the target obstacle based on the first polygon and the second polygon, is used for: If the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the target obstacle is determined to be the first single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the target obstacle is determined to be the second single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the step depth is determined based on the positional relationship between the first polygon and the second polygon. The height data of the target obstacle is determined based on the step depth.

[0147] This application provides a possible implementation method in which each location region is a rectangular region, and the first polygon and the second polygon mentioned above are both rectangles; When determining the step depth based on the positional relationship between the first polygon and the second polygon, the aforementioned acquisition module 901 is used for: Determine the target location of the mobile device at the moment of real-time spatial information acquisition; Determine the first target edge in the first polygon that is on the same side as the target position, and the second target edge in the second polygon that is on the same side as the target position; The horizontal distance between the first target edge and the second target edge is taken as the step depth.

[0148] This application embodiment provides a possible implementation method in which the acquisition module 901, when determining the height data of the target obstacle based on the step depth, is used for: If the step depth is greater than the target depth threshold, the height data is determined to be of the first double-layer type; Otherwise, determine the height data as the second double-layer type.

[0149] This application provides a possible implementation method, wherein the above clustering conditions include: The first side of the target polygon is longer than a preset length threshold, and the second side of the target polygon is longer than a preset width threshold; wherein, the target polygon is either a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon that is on the same side as the target position, and the second side length is the side length of the second side of the target polygon that is adjacent to the first side.

[0150] This application provides a possible implementation method, in which the self-moving device further includes an obstacle-crossing assist device; When the control module 902 controls the self-moving device to cross or bypass the target obstacle based on altitude data, it is used for: Based on altitude data, the self-moving device is controlled to cross or bypass target obstacles, and the working state of the obstacle crossing assistance device is controlled during the movement; the working state is either the obstacle crossing assistance state or the storage state.

[0151] This application embodiment provides a possible implementation method in which the control module 902, when controlling the self-moving device to cross or bypass the target obstacle based on altitude data and controlling the working state of the obstacle-crossing assistance device during movement, is used to: If the height data is of the first single-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to the storage state during the movement; If the height data is of the second single-layer type or the second double-layer type, control the self-moving device to bypass the target obstacle, and control the obstacle-crossing assist device to be in the storage state during the movement. If the height data is of the first double-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to the obstacle crossing assist state during the movement.

[0152] This application provides a possible implementation method, wherein the target obstacle includes a threshold; When acquiring the area height data of multiple location regions of the target obstacle, the aforementioned acquisition module 901 is used for: Image data acquired from the mobile device in the pre-movement direction; If a threshold is identified based on image data, obtain the regional height data of multiple location areas of the threshold.

[0153] The apparatus in this application embodiment can execute the method provided in this application embodiment, and the implementation principle is similar. The actions performed by each module in the apparatus of each embodiment of this application correspond to the steps in the method of each embodiment of this application. For detailed functional descriptions of each module of the apparatus, please refer to the descriptions in the corresponding methods shown above, which will not be repeated here.

[0154] This application embodiment can acquire regional height data of multiple location areas of a target obstacle during the movement of the self-moving device, and determine the height data of the target obstacle based on the height data of each region; during the movement of the self-moving device, it can control the self-moving device to cross or avoid the target obstacle based on the height data; this application refines the data granularity and improves the data representation capability by using regional height data of multiple location areas, making the obstacle height data determined by the height data of each region more accurate, thereby improving the movement control capability of the self-moving device; at the same time, this application can also greatly reduce the obstacle crossing failure rate of the self-moving device, further improving the work efficiency.

[0155] This application provides an electronic device, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of a control method for a self-moving device. Compared with related technologies, this application can achieve the following: During the movement of the self-moving device, it can acquire regional height data of multiple location areas of a target obstacle to determine the height data of the target obstacle based on the height data of each region; during the movement of the self-moving device, it can control the self-moving device to cross or avoid the target obstacle based on the height data; this application refines the data granularity and improves the data representation capability by using regional height data of multiple location areas, making the obstacle height data determined by each region height data more accurate and improving the movement control capability of the self-moving device; at the same time, this application can also greatly reduce the obstacle crossing failure rate of the self-moving device, further improving operational efficiency.

[0156] In one alternative embodiment, an electronic device is provided, such as Figure 10 As shown, Figure 10 The illustrated electronic device 100 includes a processor 1001 and a memory 1003. The processor 1001 and the memory 1003 are connected, for example, via a bus 1002. Optionally, the electronic device 100 may further include a transceiver 1004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 1004 is not limited to one type, and the structure of the electronic device 100 does not constitute a limitation on the embodiments of this application.

[0157] Processor 1001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, 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. Processor 1001 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0158] Bus 1002 may include a pathway for transmitting information between the aforementioned components. Bus 1002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 1002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 10 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0159] The memory 1003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium capable of carrying or storing computer programs and capable of being read by a computer, without limitation herein.

[0160] The memory 1003 is used to store computer programs that execute the embodiments of this application, and the execution is controlled by the processor 1001. The processor 1001 is used to execute the computer programs stored in the memory 1003 to implement the steps shown in the foregoing method embodiments.

[0161] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, and tablets, as well as fixed terminals such as digital TVs and desktop computers.

[0162] This application provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the steps of the control method for the self-moving device of this application.

[0163] This application provides a computer program product including instructions that, when executed, cause a computer to perform the steps of the self-moving device control method of this application.

[0164] The above description does not provide detailed technical specifications regarding the structure of each layer. However, those skilled in the art should understand that layers and regions of desired shapes can be formed using various technical means. Furthermore, to form the same structure, those skilled in the art can also design methods that are not entirely identical to those described above. Additionally, although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be advantageously combined.

[0165] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0166] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A control method for a self-moving device, characterized in that, include: During the movement of the self-moving device, regional height data of multiple location areas of the target obstacle are acquired; The height data of the target obstacle is determined based on the regional height data of multiple location areas; Based on the altitude data, the self-moving device is controlled to cross or bypass the target obstacle.

2. The method according to claim 1, characterized in that, The self-moving device includes a device body, on which a spatial information sensor is provided; The acquisition of regional height data for multiple location areas of the target obstacle includes: Acquire real-time spatial information of the target obstacle collected by the spatial information sensor; Based on the real-time spatial information, the regional height data of multiple location areas of the target obstacle are determined.

3. The method according to claim 2, characterized in that, The area height data includes height values; The determination of the height data of the target obstacle based on regional height data from multiple location areas includes: The region height type of the corresponding location area is determined based on the height value; Clustering is performed on each of the location regions based on the region height type to obtain the height data of the target obstacle.

4. The method according to claim 3, characterized in that, The area height types include a first type, a second type, and a third type; The process of determining the region height type based on the height value includes: If the height value of the location region is greater than the first height threshold and not greater than the second height threshold, then the region height type of the corresponding location region is determined to be the first type; If the height value of the location region is greater than the second height threshold and not greater than the third height threshold, then the region height type of the corresponding location region is determined to be the second type. If the height value of the location region is greater than the third height threshold, then the region height type of the corresponding location region is determined to be the third type; wherein, the first height threshold is less than the second height threshold, and the second height threshold is less than the third height threshold.

5. The method according to claim 4, characterized in that, The process of clustering each location region based on the region height type to obtain the height data of the target obstacle includes: For each first location region corresponding to the first type and each second location region corresponding to the second type, a first polygon is generated; wherein the first polygon covers all the first location regions and the second location regions, and the area of ​​the first polygon is less than a preset first threshold. For each second location region corresponding to the second type, a second polygon is generated; wherein the second polygon covers all second location regions, and the area of ​​the second polygon is less than a preset second threshold. The height data of the target obstacle is determined based on the first polygon and the second polygon.

6. The method according to claim 5, characterized in that, The step of determining the height data of the target obstacle based on the first polygon and the second polygon includes: If the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the target obstacle is determined to be the first single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the target obstacle is determined to be the second single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the step depth is determined based on the positional relationship between the first polygon and the second polygon. The height data of the target obstacle is determined based on the stepped depth.

7. The method according to claim 6, characterized in that, Each of the aforementioned location regions is a rectangular region, and both the first polygon and the second polygon are rectangles; Determining the step depth based on the positional relationship between the first polygon and the second polygon includes: Determine the target location of the self-moving device at the time of acquisition of the real-time spatial information; Determine the first target edge in the first polygon that is on the same side as the target position, and the second target edge in the second polygon that is on the same side as the target position; The horizontal distance between the first target edge and the second target edge is taken as the step depth.

8. The method according to claim 6, characterized in that, The determination of the height data of the target obstacle based on the step depth includes: If the step depth is greater than the target depth threshold, then the height data is determined to be of the first double-layer type; Otherwise, the height data is determined to be of the second dual-layer type.

9. The method according to claim 7, characterized in that, The clustering conditions include: The first side of the target polygon is longer than a preset length threshold, and the second side of the target polygon is longer than a preset width threshold; wherein, the target polygon is a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon that is on the same side as the target position, and the second side length is the side length of the second side of the target polygon that is adjacent to the first side.

10. The method according to claim 8, characterized in that, The self-moving device also includes an obstacle-crossing assist device; The method of controlling the self-moving device to cross or bypass the target obstacle based on the height data includes: Based on the height data, the self-moving device is controlled to cross or bypass the target obstacle, and the working state of the obstacle crossing assist device is controlled during the movement; wherein, the working state is an obstacle crossing assist state or a storage state.

11. The method according to claim 10, characterized in that, The method of controlling the self-moving device to cross or bypass the target obstacle based on the height data, and controlling the working state of the obstacle-crossing assistance device during movement, includes: If the height data is of the first single-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to be the storage state during the movement; If the height data is of the second single-layer type or the second double-layer type, then control the self-moving device to bypass the target obstacle, and control the working state of the obstacle-crossing assist device to be in the storage state during the movement; If the height data is of the first dual-layer type, then the self-moving device is controlled to cross the target obstacle, and during the movement, the working state of the obstacle crossing assist device is controlled to be the obstacle crossing assist state.

12. The method according to claim 1, characterized in that, The target obstacle includes a threshold; The acquisition of regional height data for multiple location areas of the target obstacle includes: Acquire image data of the self-moving device in the pre-moving direction; If a threshold is identified based on the image data, then the regional height data of multiple location areas of the threshold is obtained.

13. A control device for a self-moving device, characterized in that, The device includes: The acquisition module is used to acquire regional height data of multiple location areas of the target obstacle during the movement of the self-moving device; and to determine the height data of the target obstacle based on the regional height data of the multiple location areas. The control module is used to control the self-moving device to cross or bypass the target obstacle based on the height data.

14. The apparatus according to claim 13, characterized in that, The self-moving device includes a device body, on which a spatial information sensor is provided; When acquiring the regional height data of multiple location areas of the target obstacle, the acquisition module is used for: Acquire real-time spatial information of the target obstacle collected by the spatial information sensor; Based on the real-time spatial information, the regional height data of multiple location areas of the target obstacle are determined.

15. The apparatus according to claim 14, characterized in that, The area height data includes height values; When the acquisition module determines the height data of the target obstacle based on regional height data from multiple location areas, it is used for: The region height type of the corresponding location area is determined based on the height value; Clustering is performed on each of the location regions based on the region height type to obtain the height data of the target obstacle.

16. The apparatus according to claim 15, characterized in that, The height types include a first type, a second type, and a third type; When determining the region height type of the corresponding location area based on the height value, the acquisition module is used for: If the height value of the location region is greater than the first height threshold and not greater than the second height threshold, then the region height type of the corresponding location region is determined to be the first type; If the height value of the location region is greater than the second height threshold and not greater than the third height threshold, then the region height type of the corresponding location region is determined to be the second type. If the height value of the location region is greater than the third height threshold, then the region height type of the corresponding location region is determined to be the third type; wherein, the first height threshold is less than the second height threshold, and the second height threshold is less than the third height threshold.

17. The apparatus according to claim 16, characterized in that, When the acquisition module performs clustering processing on each of the location regions based on the region height type to obtain the height data of the target obstacle, it is used for: For each first location region corresponding to the first type and each second location region corresponding to the second type, a first polygon is generated; wherein the first polygon covers all the first location regions and the second location regions, and the area of ​​the first polygon is less than a preset first threshold. For each second location region corresponding to the second type, a second polygon is generated; wherein the second polygon covers all second location regions, and the area of ​​the second polygon is less than a preset second threshold. The height data of the target obstacle is determined based on the first polygon and the second polygon.

18. The apparatus according to claim 17, characterized in that, When determining the height data of the target obstacle based on the first polygon and the second polygon, the acquisition module is used to: If the side length of the first polygon meets the preset clustering conditions, but the side length of the second polygon does not meet the preset clustering conditions, then the height data of the target obstacle is determined to be the first single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the areas of the first polygon and the second polygon are the same, then the height data of the target obstacle is determined to be the second single-layer type. If the side lengths of the first polygon and the second polygon both satisfy the preset clustering conditions, and the area of ​​the first polygon is greater than the area of ​​the second polygon, then the step depth is determined based on the positional relationship between the first polygon and the second polygon. The height data of the target obstacle is determined based on the stepped depth.

19. The apparatus according to claim 18, characterized in that, Each of the aforementioned location regions is a rectangular region, and both the first polygon and the second polygon are rectangles; When determining the step depth based on the positional relationship between the first polygon and the second polygon, the acquisition module is used for: Determine the target location of the self-moving device at the time of acquisition of the real-time spatial information; Determine the first target edge in the first polygon that is on the same side as the target position, and the second target edge in the second polygon that is on the same side as the target position; The horizontal distance between the first target edge and the second target edge is taken as the step depth.

20. The apparatus according to claim 18, characterized in that, When determining the height data of the target obstacle based on the step depth, the acquisition module is used for: If the step depth is greater than the target depth threshold, then the height data is determined to be of the first double-layer type; Otherwise, the height data is determined to be of the second dual-layer type.

21. The apparatus according to claim 19, characterized in that, The clustering conditions include: The first side of the target polygon is longer than a preset length threshold, and the second side of the target polygon is longer than a preset width threshold; wherein, the target polygon is a first polygon or a second polygon; the first side length is the side length of the first side of the target polygon that is on the same side as the target position, and the second side length is the side length of the second side of the target polygon that is adjacent to the first side.

22. The apparatus according to claim 20, characterized in that, The self-moving device also includes an obstacle-crossing assist device; When the control module controls the self-moving device to pass over or around the target obstacle based on the height data, it is used to: Based on the height data, the self-moving device is controlled to cross or bypass the target obstacle, and the working state of the obstacle crossing assist device is controlled during the movement; wherein, the working state is an obstacle crossing assist state or a storage state.

23. The apparatus according to claim 22, characterized in that, When the control module controls the self-moving device to cross or bypass the target obstacle based on the height data, and controls the working state of the obstacle-crossing assistance device during movement, it is used for: If the height data is of the first single-layer type, then control the self-moving device to cross the target obstacle, and control the working state of the obstacle crossing assist device to be the storage state during the movement; If the height data is of the second single-layer type or the second double-layer type, then control the self-moving device to bypass the target obstacle, and control the working state of the obstacle-crossing assist device to be in the storage state during the movement; If the height data is of the first dual-layer type, then the self-moving device is controlled to cross the target obstacle, and during the movement, the working state of the obstacle crossing assist device is controlled to be the obstacle crossing assist state.

24. The apparatus according to claim 13, characterized in that, The target obstacle includes a threshold; When acquiring the regional height data of multiple location areas of the target obstacle, the acquisition module is used for: Acquire image data of the self-moving device in the pre-moving direction; If a threshold is identified based on the image data, then the regional height data of multiple location areas of the threshold is obtained.

25. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-12.

26. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-12.

27. A computer program product, characterized in that, The computer program product includes instructions that, when executed, cause a computer to perform the method of any one of claims 1-12.

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