Control method of autonomous working system and autonomous working system

Abstract

A control method of an autonomous working system, a map acquisition method, a control method of an autonomous robot, and an autonomous working system wherein the control method of the autonomous working system comprises: acquiring environmental information collected over a target area (S901), the environmental information comprising image data and position data; generating a map of the target area based on the environmental information (S902), the map comprising at least one type of attribute information, the attribute information being associated with a specific area in the map; and generating a working strategy of the autonomous robot in the target area based on the attribute information (S903). By adopting the mode, the accurate and comprehensive map can be quickly obtained, so that the complete work of the working area is realized.

Description

Control methods for autonomous working systems and autonomous working systems Technical Field

[0001] This application relates to the technical field of aerial mapping equipment, and in particular to a control method for an autonomous operating system and the autonomous operating system itself. Background Technology

[0002] With the development of agricultural mechanization and smart homes, autonomous robots, such as automatic lawnmowers, are gradually entering people's lives as efficient and convenient yard maintenance equipment. Automatic lawnmowers, through built-in sensors, navigation systems, and intelligent control algorithms, can autonomously plan paths, avoid obstacles, and operate on a timed schedule without human intervention. This achieves increased lawn coverage, improved mowing efficiency, and reduced energy consumption, significantly enhancing the level of intelligence in yard gardening. Autonomous robots can also refer to other devices capable of autonomous operation, such as automatic snowplows and automatic mopping robots. Summary of the Invention

[0003] To overcome the shortcomings of existing technologies, this application provides a control method for an autonomous working system, which may include:

[0004] The system acquires environmental information collected over a target area, including image data and location data; generates a map of the target area based on the environmental information, wherein the map includes at least one attribute information associated with a specific area in the map; and generates a working strategy for the autonomous robot in the target area based on the attribute information.

[0005] Using the above method, an accurate and comprehensive map can be obtained quickly, thereby enabling complete work in the work area.

[0006] To overcome the shortcomings of existing technologies, this application provides a control method for an autonomous working system, which may include:

[0007] This control method can quickly obtain accurate and comprehensive maps, thereby enabling complete operation of the work area.

[0008] To overcome the shortcomings of existing technologies, this application provides a map acquisition method, which may include:

[0009] Acquire environmental information collected over the target area, including image data and location data;

[0010] A map of the target area is generated based on environmental information, wherein the map contains at least one attribute information, and the attribute information is associated with a specific area in the map.

[0011] This map acquisition method can quickly produce accurate and comprehensive maps.

[0012] To overcome the shortcomings of existing technologies, this application provides a control method for an autonomous robot, which may include:

[0013] Obtain a map of the target area, which includes multiple sub-regions, each containing at least one attribute; establish a mapping relationship between the attribute information and the work strategy; and configure corresponding work strategies for sub-regions with different attributes based on the mapping relationship.

[0014] This control method can quickly obtain accurate and comprehensive maps, thereby enabling complete operation of the work area.

[0015] To overcome the shortcomings of the prior art, this application provides a mapping method, mapping system and storage medium for a work area, which can efficiently and accurately create a map of the work area.

[0016] According to a first aspect of this embodiment, a method for mapping a work area is provided, the work area being in which an autonomous machine can move and / or work, the method comprising:

[0017] A three-dimensional map of the work area is obtained using aerial photography equipment, and the three-dimensional map includes the coordinate information of the work area.

[0018] A work area map recognizable by the autonomous machine is generated based on the 3D map, the work area map including at least the boundary of the work area; the autonomous machine moves and / or works in the work area based on the work area map.

[0019] In one embodiment, generating a work area map recognizable by the autonomous machine based on the 3D map includes:

[0020] The 3D map is transmitted to a user-operable device, which is configured to provide the user with an interface for manipulating the 3D map.

[0021] The work area map is generated based on the user's operations on the 3D map.

[0022] In one embodiment, generating the work area map based on user operations on the 3D map includes:

[0023] The boundaries of the work area map are generated based on at least three boundary points in the 3D map selected by the user on the interface.

[0024] In one embodiment, generating the work area map based on user operations on the 3D map includes:

[0025] Based on the areas that the user delineates in the 3D map that are accessible or inaccessible on the interface, the autonomous work machine is generated in the work area map as an area that is accessible or inaccessible.

[0026] In one embodiment, generating the work area map based on user operations on the 3D map includes:

[0027] Based on the channels in the 3D map marked by the user on the interface, channels in the work area map are generated.

[0028] In one embodiment, generating the work area map based on user operations on the 3D map includes:

[0029] Based on the charging stations marked by the user on the interface in the 3D map, charging stations in the work area map are generated, and the charging stations are configured to provide charging services for at least autonomous working machines.

[0030] In one embodiment, a work area map recognizable by the autonomous machine is generated based on the 3D map, including...

[0031] The boundaries of the work area are automatically identified based on the 3D map, and the boundaries of the work area map are generated.

[0032] In one embodiment, the boundaries of the work area map are transmitted to a user-operable device, the device being configured to provide the user with an interface for manipulating the work area map;

[0033] The boundaries of the work area map are corrected based on the user's operations on the map's boundaries.

[0034] In one embodiment, the mapping method further includes:

[0035] At least one of the information of the shaded area, the slope area, and the pothole area in the 3D map is automatically or marked in the working area map by user operation. The information of the shaded area includes at least the location and / or shape of the shaded area, the information of the slope area includes at least the location and / or slope of the slope area, and the information of the pothole area includes at least the location of the pothole area.

[0036] In one embodiment, the method of transmitting the 3D map to a user-operable device includes:

[0037] The 3D map is directly transmitted to a user-operable device.

[0038] Alternatively, the 3D map can be transmitted to a server or cloud, and the user can operate the device to retrieve the 3D map from the server or cloud.

[0039] In one embodiment, acquiring a three-dimensional map of the work area via aerial photography includes:

[0040] Control the aerial photography equipment to capture two-dimensional images of the work area from different directions at preset aerial photography angles;

[0041] A three-dimensional map of the working area is generated based on the two-dimensional image of the target area.

[0042] In one embodiment, acquiring a three-dimensional map of the work area via aerial photography includes:

[0043] Define a target area on an existing map, the target area including the work area;

[0044] The aerial photography equipment is controlled to capture two-dimensional images of the target area from different directions at preset aerial photography angles.

[0045] A three-dimensional map of the target area is generated based on the two-dimensional image of the target area.

[0046] In one embodiment, controlling the aerial photography equipment to capture images of the work area from different directions of the target area at preset aerial angles includes:

[0047] The aerial photography equipment is controlled to begin filming at a preset distance or preset time before entering the target area.

[0048] The aerial photography equipment is controlled to fly along a preset flight path and capture images of the target area. With the area directly above the target area as a reference, the flight path covers at least one side of the relative boundaries of the target area.

[0049] On the other hand, a mapping system is provided, including aerial photography equipment and map generation equipment, wherein the aerial photography equipment is configured to fly and operate at least within a work area, and the aerial photography equipment includes:

[0050] An imaging sensor is configured to capture images of the working area;

[0051] The first locator is configured to acquire the coordinate information of the aerial photography equipment;

[0052] A first controller is configured to acquire an image of the work area and the coordinate information, and generate a three-dimensional map of the work area, the three-dimensional map including the coordinate information of the work area;

[0053] The map generation device includes:

[0054] The second controller is configured to acquire the three-dimensional map and generate a work area map that can be recognized by the autonomous working machine based on the three-dimensional map, the work area map including at least the boundary of the work area;

[0055] The autonomous working machine moves and / or works in the work area based on the work area map.

[0056] In the technical solution provided in this application embodiment, a three-dimensional map of the work area is acquired using aerial photography equipment. This three-dimensional map covers the complete terrain and boundary features of the work area. The aerial photography equipment has a locator, so the images it captures contain coordinate information. Therefore, the three-dimensional map generated based on these images also contains coordinate information. This process converts the three-dimensional map carrying complete information about the work area into a two-dimensional map (work area map) that can be recognized by the autonomous machine, making the work area map more accurate. This more accurate work area map allows the autonomous machine to move and work more precisely and intelligently within the work area. Furthermore, since the time required for aerial photography equipment to traverse the work area is significantly reduced compared to manual traversal, the efficiency of mapping is greatly improved, further saving labor costs.

[0057] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0058] The objectives, technical solutions, and beneficial effects of this application described above can be clearly obtained through the following detailed description of specific embodiments that enable the implementation of this application, in conjunction with the accompanying drawings.

[0059] The same reference numerals and symbols in the accompanying drawings and the specification are used to represent the same or equivalent elements.

[0060] Figure 1 is a schematic diagram of a mapping system provided in an embodiment of this application;

[0061] Figure 2 is a flowchart illustrating a method for mapping a work area according to an embodiment of this application;

[0062] Figure 3 is a schematic diagram of the process of generating a three-dimensional map in the mapping method of the work area provided in an embodiment of this application;

[0063] Figure 4 is a schematic diagram of the process of generating a three-dimensional map in the mapping method of the working area provided in an embodiment of this application;

[0064] Figure 5 is a flowchart of the operation of the aerial photography equipment in the embodiment described in Figure 4;

[0065] Figure 6 is a schematic flowchart of the process of generating a work area map in a work area mapping method provided in an embodiment of this application;

[0066] Figure 7 is a schematic diagram of an autonomous working system in one embodiment of this application;

[0067] Figure 8 is a schematic diagram of an application scenario in one embodiment of this application;

[0068] Figure 9 is a schematic diagram of a control method for an autonomous working system according to an embodiment of this application. Specific Implementation

[0069] To facilitate understanding of this application, the technical solutions in the embodiments of this specification will be clearly and completely 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. The purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. 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.

[0070] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Furthermore, unless expressly specified otherwise, the technical features in the various embodiments of this application can be considered as capable of being combined or integrated with each other, provided that such combination or integration is not technically impossible to implement.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0072] In practical applications, autonomous robots typically move autonomously within a pre-defined work area. This boundary is generally established by a human carrying or remotely controlling a positioning device along the edge of the work area. During movement, the positioning device records its position coordinates, which are used to determine the boundary of the work area. The positioning device can be a satellite positioning module or an autonomous robot equipped with one. However, to obtain detailed map information within the area, such as the locations of obstacles, passageways, and charging stations, a human must again carry the positioning device to collect data. This mapping method relies on continuous human intervention, is time-consuming, labor-intensive, and inefficient. Furthermore, when the positioning signal is weak or interfered with, the accuracy of the collected coordinates is affected, leading to a decrease in the accuracy of the boundary and map data. Simultaneously, this method struggles to acquire information about terrain changes such as slope and potholes, limiting subsequent path planning and environmental perception capabilities.

[0073] Considering the aforementioned shortcomings, as shown in Figure 7, this application proposes an autonomous working system 3. This autonomous working system may include: a data processing system 31, configured to acquire environmental information collected over a target area, including image information and location information; and a map of the target area generated based on the environmental information, wherein the map includes at least one attribute information associated with a specific area in the map. A working strategy generation system 32 is configured to generate a working strategy for the autonomous robot in the target area based on the attribute information. In this application embodiment, a map of the target area is generated based on the environmental information, and the working strategy for the autonomous robot in the target area is determined based on the attribute information in the generated map. Using this method, an accurate and comprehensive map can be obtained quickly, thereby enabling complete operation of the working area.

[0074] In some embodiments, the autonomous operating system 3 may further include an autonomous flight device 30, configured to collect environmental information of the target area via multiple sensors during flight in the target area. The autonomous flight device can quickly obtain accurate and comprehensive maps.

[0075] The autonomous flight device 30 is configured to fly and operate at least within the work area. The autonomous flight device 30 can be a drone, helicopter, hot air balloon, small spacecraft, rocket, kite, parachute, etc. In this embodiment, the autonomous flight device 30 can be a drone. In some places below, the autonomous flight device is also referred to as aerial photography equipment.

[0076] The autonomous flight device 30 is equipped with multiple sensors, including at least an image acquisition sensor 301 and a satellite positioning sensor 302. The image acquisition sensor 301 is configured to capture image information of the target area; the satellite positioning sensor 302 is configured to acquire the location information of the autonomous flight device. During flight within the target area, the autonomous flight device also collects environmental information about the target area using these multiple sensors. The multiple sensors may further include a lidar sensor or an ultrasonic sensor for measuring changes in terrain altitude. The multiple sensors may be at least two of the aforementioned sensors, such as the image acquisition sensor and the lidar sensor. This application does not limit this to any particular type.

[0077] In some embodiments, the target area can be a golf course, a large lawn, or the lawns of several users within the same community. Since the users have purchased lawn maintenance services, the supplier needs to maintain the lawns of these users at the same time.

[0078] In some embodiments, the autonomous flight device 30 needs to acquire the target area to be flown before operation. During the flight from the starting point to the ending point of the target area, it plans a flight path based on target environmental information collected by multiple sensors. During the flight according to the flight path, it collects environmental information of the target area through multiple sensors. The autonomous flight device stores multiple target environmental information items and multiple flight paths associated with these items. In this embodiment, the user selects the target area to be flown. After the drone acquires the target area, it flies from its current position to the starting point of the target area and plans a flight path based on the collected target environmental information. For example, when surveying a green area with no undulations, the drone is controlled to fly along a high-density grid path. This is because the data acquisition requirements are high, allowing the image acquisition sensor to capture micro-topographical changes during flight. When surveying a fairway area with some undulations, the drone is controlled to fly along a medium-density "S" or "Z" shaped path. Compared to the green, the data acquisition requirements are slightly lower, so this method is suitable. When surveying areas with tall rough (half-rough or long rough), the drone is controlled to fly along a low-density coverage path to achieve efficient data acquisition during flight. By adjusting the flight path using the above adaptive adjustment method for different types of areas, the mapping of the target area can be completed while ensuring mapping accuracy for different types of areas.

[0079] In other embodiments, the autonomous flight device 30 needs to acquire the target area and flight path before operation. During the flight from the starting point to the ending point of the target area, it collects environmental information of the target area through multiple sensors. That is, it controls the autonomous flight device 30 to fly and operate within the selected target area. Specifically, the target area is defined on an existing map, and the target area includes the work area. The autonomous flight device 30 can identify the target area, and its image acquisition sensor 301 is configured to capture two-dimensional images of the target area from different directions at a preset aerial angle. A three-dimensional map of the target area is generated based on the two-dimensional images. The existing map can be Google Maps, Gaode Maps, Baidu Maps, etc. The user defines the target area on an existing map, and the target area completely covers the work area. The autonomous flight device 30 can fly based on the user-defined target area, capturing two-dimensional images of the entire target area from different directions, including the complete two-dimensional image of the work area. In this embodiment, the drone is controlled to fly along a pre-planned path to achieve rapid mapping.

[0080] Of course, drones can also fly and collect images of the target area using other methods described below.

[0081] In some embodiments, during the flight of the autonomous flight device 30, the image acquisition sensor 301 is configured to capture multiple two-dimensional images of the work area from different directions of the work area at preset aerial angles, including but not limited to at least one of orthophoto images, oblique images, and close-up images.

[0082] In some embodiments, during the flight of the UAV in the target area, flight parameters can be adjusted based on environmental information. These flight parameters may include, but are not limited to, at least one of the following: flight altitude, the density of environmental information collection, and image parameters. During flight according to the adjusted flight parameters, environmental information of the target area is collected through multiple sensors. Specifically, when the environmental information indicates that the surface of the currently collected area is a nearly flat green, the flight altitude is adjusted to optimize the data collection resolution; or, when complex terrain areas are identified, the sampling density is increased; or, when changes in lighting conditions are identified, image parameters are adjusted to reduce exposure. It is worth noting that the process of adjusting flight parameters can be performed simultaneously with the path planning process, or they can exist independently; this application does not limit this.

[0083] In some embodiments, the autonomous working system 3 may include a data processing system 31. The data processing system 31 may be configured to receive environmental information and generate a map of the target area based on the environmental information. The data processing system 31 may be a processor with data processing capabilities. The data processing system 31 may be located in the autonomous flight device, the autonomous robot, or the server; or, it may be distributed among any of these three devices, or it may be partially located in the autonomous flight device, the autonomous robot, and the server, respectively.

[0084] In some embodiments, the data processing system 31 in the autonomous working system can perform georegistration of image information based on location information to generate a map of the target area.

[0085] In other embodiments, the data processing system 31 can stitch the acquired images to obtain a stitched image; then, by combining the acquired location information and IMU (Inertial Measurement Unit) data, it can optimize the attitude and position of the stitched image; and finally, it can synthesize the stitched and optimized images into a two-dimensional or three-dimensional map.

[0086] In other embodiments, the data processing system 31 may be configured to acquire an image and coordinate information of a work area, and generate a three-dimensional map of the work area, the three-dimensional map including the coordinate information of the work area. The coordinate information of the work area includes the longitude and latitude of any point within the work area. In some embodiments, the coordinate information may also include the altitude of any point within the work area.

[0087] In some embodiments, after obtaining a map of the target area, the map can be format-converted and / or its coordinates calibrated to generate a map conforming to the format of the autonomous robot navigation system. Thus, the autonomous robot can use the map to perform its tasks.

[0088] In some embodiments, the data processing system can also be configured to determine attribute information based on environmental information collected by the autonomous flight device. That is, after collecting environmental information, attribute information can be marked on a map based on the environmental information. Subsequently, a working strategy for the autonomous robot in multiple working areas can be generated based on the map marked with attribute information.

[0089] In other embodiments, attribute information can be determined based on user input. For example, the user can directly designate an area as a no-entry zone for the robot.

[0090] In some embodiments, attribute information may include, but is not limited to, at least one of: region type, terrain features, environmental features, and functional features. Attribute information may further include at least one of the terrain feature classification, environmental feature classification, and functional feature classification.

[0091] Area types may include, but are not limited to, at least two of the following: bunkers, greens, green perimeters, fairways, rough, and long rough.

[0092] In some embodiments, the target area can be divided into multiple sub-regions based on attribute information, and each sub-region includes at least one attribute. That is, the sub-region can be a fairway attribute.

[0093] Topographic features may include, but are not limited to: elevation information, i.e., altitude data of ground points; slope information, i.e., the degree of inclination and aspect of the land surface; topographic relief, i.e., the degree of elevation change within a region; aspect information, i.e., the angle of slope orientation (north, east, south, west, etc.); topographic curvature, i.e., the degree of curvature of the land surface (convexity, concavity); surface roughness, i.e., surface texture and micro-topographic variations; watershed boundaries, i.e., watershed boundaries and catchment areas; visibility analysis, i.e., the impact of topography on visual obstruction; and slope length factor, i.e., the slope length parameter in soil and water conservation calculations.

[0094] Environmental characteristics may include, but are not limited to: satellite positioning signal quality, i.e., GPS / GNSS signal strength, accuracy, and reliability; positioning mode type, i.e., single-point positioning, differential positioning, RTK, etc.; number of satellites, i.e., the number and geometric distribution of visible satellites; data sampling rate, i.e., the temporal resolution of location data; receiver type, i.e., single-frequency, dual-frequency, and multi-frequency receivers; base station distance, i.e., the distance to the differential reference station; signal obstruction level, i.e., the impact of buildings and vegetation on the signal; and lawn density, i.e., the coverage and distribution of lawns within the area. The indicators include: lawn health index (indicators of lawn growth status, chlorophyll content, etc.); NDVI index (Normalized Difference Vegetation Index, reflecting vegetation vitality); vegetation height (vertical height of lawn and other vegetation); leaf area index (LAI, total leaf area per unit area); biomass estimation (dry or fresh weight of vegetation); soil moisture (soil water content affecting vegetation growth); vegetation cover (percentage of vegetation covering the surface); phenological information (seasonal growth changes of vegetation); and pest and disease monitoring (identification of threats to vegetation health).

[0095] Functional features may include at least one task feature to be performed, such as watering, mowing, shoveling snow, or removing insects.

[0096] In some embodiments, the environment type includes satellite signal obstruction, and the data processing system is further configured to: process the acquired image information to identify obstacles affecting the quality of satellite positioning signals; calculate the obstruction range of the obstacles based on at least one of the obstacle's position, height, shape parameters, and distribution density; and determine the working area where the satellite positioning signal quality is less than a preset signal quality threshold based on the obstruction range. In this embodiment, by identifying tall obstacles in the image, such as slopes and trees that can form shadows, and combining this with time or the angle of sunlight, the range in which the obstacle will form a shadow can be determined. Thus, the corresponding range can be marked as a shadow attribute on the map, or as an attribute where the satellite positioning signal quality is less than a preset quality threshold. Compared to identifying shadows during robot movement, the method in this embodiment can achieve the purpose of quickly marking shadow areas on the map.

[0097] In other embodiments, shadow areas can be directly identified by recognizing shadows in an image, and the time of image acquisition can be recorded.

[0098] In some embodiments, the autonomous flight device can be controlled to collect environmental information of the target area at preset time intervals. Subsequently, when the autonomous robot needs to use a map, the map can be updated to the latest version. This allows the autonomous robot to perform tasks according to the latest map, ensuring the accuracy of the work strategies generated by the subsequent work strategy generation system.

[0099] In some embodiments, the autonomous working system may include a working strategy generation system 32, which can be configured to generate working strategies for the autonomous robot in multiple working areas based on attribute information.

[0100] The work strategy generation system 32 can be a processor with data processing capabilities. The work strategy generation system 32 can be installed in an autonomous flight device, an autonomous robot, or a server; or, it can be installed in a distributed manner in any of these three devices, or it can be partially installed in the autonomous flight device, the autonomous robot, and the server respectively.

[0101] After receiving the work strategy, the server sends it to the corresponding robot to control the robot with the task to perform the corresponding work. Alternatively, the robot generates the work strategy and sends it to itself and other robots to control that robot or the robot with the task to perform the corresponding work.

[0102] In some embodiments, the autonomous robot can be a device capable of operating automatically, such as an automatic lawnmower or an automatic snowplow. In the following description, an automatic lawnmower will be used as an example of an autonomous robot.

[0103] In some embodiments, the work strategy generation system 32 can establish a mapping relationship between attribute information and work strategies, and configure corresponding work strategies for sub-regions with different attributes according to the mapping relationship.

[0104] In some embodiments, the multiple work areas may include at least a first area having a first attribute and a second area having a second attribute, wherein the work strategy generation system is configured to: control the autonomous robot to move in the first area based on first work parameters; and control the autonomous robot to move in the second area based on second work parameters, wherein the first work parameters are different from the second work parameters. By controlling the robot to perform work using different work parameters for areas with different attributes, the work effect can be ensured to meet the requirements of different work areas.

[0105] In some embodiments, the first or second operating parameter may include, but is not limited to, at least one of the following: mowing quality parameters, motion control parameters, and path planning parameters. The mowing quality parameters include at least one of working height and blade rotation speed; the motion control parameters include at least one of movement speed, movement direction, turning radius, and acceleration; and the path planning parameters include at least one of adjacent path spacing, safety boundary distance, and path pattern.

[0106] For example, when the working area includes a fairway area and a half-grass area, the working height of the mowing robot's blade in the fairway area is controlled to be lower than that in the half-grass area, or the robot's movement speed in the fairway area is controlled to be lower than that in the half-grass area.

[0107] In some embodiments, when the task strategy generation system assigns tasks to the same autonomous robot based on a map, some areas in the map have attributes that the autonomous robot can handle, while others cannot. Therefore, accurate task assignment can be achieved through the following means.

[0108] In some embodiments, multiple work areas may include: a first area having a first attribute and a second area having a second attribute; the work strategy generation system may be configured to: determine whether an autonomous robot can handle the work task in the first area; and, in response to the autonomous robot being unable to handle the work task in the first area, control the autonomous robot to work in an area other than the first area. When assigning a task to an autonomous robot, the work strategy generation system determines whether the autonomous robot can handle the task in the area with the corresponding attribute. If it can, the system assigns the autonomous robot a work task in that area; if it cannot, the system does not assign the autonomous robot a work task in that area. For example: if the first area in the work area needs watering and the second area needs mowing, the system assigns a task to a lawnmower to mow the lawn in the second area.

[0109] In some embodiments, the work strategy generation system 32 acquires the work performance parameters of the autonomous robot, including type and / or capability; establishes a mapping relationship between attribute information and work performance parameters; and configures corresponding autonomous robots for sub-regions with different attributes according to the mapping relationship. The work strategy generation system 32 can control robots that meet the attribute requirements to work in the corresponding sub-regions based on their attributes. By assigning robots with corresponding work performance parameters to work areas with different attribute information, the system achieves complete work in the work areas.

[0110] The types may include, but are not limited to, at least one of snow removal, sandpit treatment, water cleaning, lawn mowing, and road sweeping.

[0111] Capabilities may include, but are not limited to, at least one of the sensor parameters, actuator parameters, and working head parameters of an autonomous robot, or other parameters determined by these parameters.

[0112] In some embodiments, establishing a mapping relationship between attribute information and working performance parameters may include, but is not limited to, at least one of the following: matching terrain attributes with robot mobility, wherein the mobility is based on the drive motor torque parameters and structural type parameters of the autonomous robot's moving components; matching functional attributes with robot operational capabilities, wherein the operational capabilities are based on the working component type parameters and operational accuracy parameters of the autonomous robot; and matching environmental attributes with robot adaptability, wherein the adaptability is based on the sensor type parameters and detection accuracy parameters of the autonomous robot.

[0113] For example, when the attribute is a terrain feature, such as slope information, the work strategy generation system can instruct an autonomous robot with a climbing ability greater than a preset climbing performance to move to a work area with a slope greater than a preset slope threshold to perform work. When the attribute information is an environmental feature, such as satellite positioning signal quality, the work strategy generation system can instruct an autonomous robot with other positioning sensors to move to a work area with satellite positioning signal quality less than a preset signal quality threshold to perform work. In this way, it can be ensured that the robot can complete all the work in the assigned area.

[0114] In some embodiments, the work strategy generation system can assess the task complexity of the work area and determine the required robot type and / or number based on the task complexity; when the capabilities of a single robot do not meet the requirements of a sub-area, multiple robots are configured to work collaboratively. That is, when one robot cannot complete the work in the work area, multiple robots can be controlled to work collaboratively.

[0115] When a single robot is slow in completing its work area, multiple robots can be controlled to work together to complete the task in that area.

[0116] When a robot is unable to complete the task in a work area due to its own operational capabilities, multiple robots with complementary capabilities can be controlled to work together to complete the task in the work area.

[0117] Specifically, when the work area includes half-grass, fairways, shade, and higher slopes, robots with high cutting capabilities can be assigned to the half-grass areas, robots with low cutting capabilities to the fairways areas, robots with vision sensors to the shaded areas, and robots with high actuation capabilities to the areas corresponding to higher slopes. These robots can then cooperate to complete the work within the designated area.

[0118] In some embodiments, for shaded areas (i.e., areas where the satellite positioning signal quality is less than a preset threshold), the work strategy generation system can assess the area of ​​the shaded area. If the area is less than the preset threshold, a robot with only satellite positioning capabilities can be controlled to move to that area to perform the cutting work, because a robot with satellite positioning capabilities can maintain the accuracy of the positioning signal in a small area.

[0119] In some embodiments, switching rules for the robot between different sub-regions can be established, including at least one of switching conditions, switching paths, and cutting parameter configurations. When there is a passage between two regions where the robot needs to work, the robot can be controlled to lift the cutter head through the passage after completing the work in the current sub-region and move to another sub-region to continue working.

[0120] In some embodiments, the autonomous work system may further include a recommendation system 33, configured to generate purchase recommendations for autonomous robots based on attribute information. The purchase recommendations may include, but are not limited to, the type and quantity of autonomous robots. For example, when the attribute information contains a shaded area, a lawnmower equipped with both visual sensors and satellite positioning sensors may be recommended for purchase. The recommendations ensure that when a work task is generated, there are sufficient autonomous robots and robots that meet the attribute requirements to complete the task.

[0121] The following describes an embodiment of this application through a specific application scenario.

[0122] Figure 8 shows a simplified partial map of a golf course, where A, B, C, and D represent the attributes of the fairway, green, rough, and shaded areas, respectively. Based on this attribute information, satellite-positioning robot 1 is assigned to the fairway area, while robot 2, combining vision and satellite positioning, is assigned to the shaded area. After robot 2 completes its work in the shaded area, a path is planned from the current area to fairway area A and then to the rough area. The planned path largely follows robot 2's movement path to avoid disrupting the original path markings. The robot is then controlled to lift its cutter head and move along these paths to return to the charging station for recharging.

[0123] As shown in Figure 9, this application also proposes a control method for an autonomous working system, which may include:

[0124] S901: Acquire environmental information collected over the target area, including image data and location data.

[0125] S902: Generate a map of the target area based on environmental information, wherein the map includes at least one attribute information, the attribute information being associated with a specific area in the map.

[0126] S903: Generate working strategies for autonomous robots in target areas based on attribute information.

[0127] The controller of this control method can be an autonomous flight device, an autonomous robot, or a server.

[0128] In some embodiments, the image data includes at least one of orthophotos, tilted images, and close-up images.

[0129] In some embodiments, image information is georeferenced based on location information to generate a map of the target area.

[0130] In some embodiments, the map of the target area is format-converted and / or its coordinates are calibrated to generate a map that matches the autonomous robot's navigation system.

[0131] In some embodiments, attribute information includes at least one of terrain features, environmental features, and functional features.

[0132] In some embodiments, the attribute information further includes at least one of terrain feature classification, environmental feature classification, and functional feature classification.

[0133] In some embodiments, the environment type includes satellite signal obstruction status, and the method includes: processing image information to identify obstacles that affect the quality of satellite positioning signals; calculating the obstruction range of obstacles based on at least one of the location, height, shape parameters and distribution density of the obstacles; and determining a working area where the satellite positioning signal quality is less than a preset signal quality threshold based on the obstruction range.

[0134] In some embodiments, the target region is divided into multiple sub-regions based on attribute information, and each sub-region includes at least one type of attribute information.

[0135] In some embodiments, generating an autonomous robot's working strategy in multiple working areas based on attribute information further includes: establishing a mapping relationship between attribute information and working strategies; and configuring corresponding working strategies for sub-regions with different attributes according to the mapping relationship.

[0136] In some embodiments, generating an autonomous robot's working strategy in multiple sub-regions based on attribute information further includes: obtaining the autonomous robot's working performance parameters, including type and / or capability; establishing a mapping relationship between attribute information and working performance parameters; and configuring corresponding autonomous robots for sub-regions with different attributes according to the mapping relationship.

[0137] In some embodiments, establishing a mapping relationship between attribute information and working performance parameters includes at least one of the following: matching terrain attributes with robot mobility, wherein the mobility is based on the drive motor torque parameters and the structural type parameters of the mobile components of the autonomous robot; matching functional attributes with robot operational capabilities, wherein the operational capabilities are based on the working component type parameters and operational accuracy parameters of the autonomous robot; and matching environmental attributes with robot adaptability, wherein the adaptability is based on the sensor type parameters and detection accuracy parameters of the autonomous robot.

[0138] In some embodiments, configuring corresponding autonomous robots for sub-regions with different attributes according to the mapping relationship further includes: assessing the task complexity of the work area and determining the required robot type and / or number based on the task complexity; when the capabilities of a single robot do not meet the requirements of the sub-region, configuring multiple robots with complementary capabilities to work collaboratively.

[0139] In some embodiments, the method includes: establishing switching rules for the robot between different sub-regions, including at least one of switching conditions, switching paths, and cutting parameter configurations.

[0140] In some embodiments, the method includes: generating purchase recommendations for autonomous robots based on attribute information, the purchase recommendations including the type and quantity of autonomous robots.

[0141] Using the above method, an accurate and comprehensive map can be obtained quickly, thereby enabling complete work in the work area.

[0142] This invention also proposes a map acquisition method, which includes:

[0143] Acquire environmental information collected over the target area, including image data and location data;

[0144] A map of the target area is generated based on environmental information, wherein the map contains at least one attribute information, and the attribute information is associated with a specific area in the map.

[0145] This map acquisition method can be applied to autonomous flight equipment, autonomous robots, and servers.

[0146] In some embodiments, the image data includes at least one of orthophotos, tilted images, and close-up images.

[0147] In some embodiments, image information is georeferenced based on location information to generate a map of the target area.

[0148] In some embodiments, the method includes: performing format conversion and / or coordinate calibration on a map of the target area to generate a map that matches the navigation system of the autonomous robot.

[0149] In some embodiments, attribute information includes at least one of terrain features, environmental features, and functional features.

[0150] In some embodiments, the attribute information further includes at least one of terrain feature classification, environmental feature classification, and functional feature classification.

[0151] In some embodiments, the environment type includes satellite signal obstruction status, and the method includes: processing image information to identify obstacles that affect the quality of satellite positioning signals; calculating the obstruction range of obstacles based on at least one of the location, height, shape parameters and distribution density of the obstacles; and determining a working area where the satellite positioning signal quality is less than a preset signal quality threshold based on the obstruction range.

[0152] In some embodiments, the target region is divided into multiple sub-regions based on attribute information, and each sub-region includes at least one type of attribute information.

[0153] Using the above method, you can quickly obtain accurate and comprehensive maps.

[0154] One embodiment of this application also proposes a control method for an autonomous robot, including:

[0155] Obtain a map of the target area, which includes multiple sub-regions, each containing at least one attribute; establish a mapping relationship between the attribute information and the work strategy; and configure corresponding work strategies for sub-regions with different attributes based on the mapping relationship.

[0156] This control method for autonomous robots can be applied to autonomous robots or servers.

[0157] In some embodiments, generating an autonomous robot's working strategy in multiple sub-regions based on attribute information further includes: obtaining the autonomous robot's working performance parameters, including type and / or capability; establishing a mapping relationship between attribute information and working performance parameters; and configuring corresponding autonomous robots for sub-regions with different attributes according to the mapping relationship.

[0158] In some embodiments, establishing a mapping relationship between attribute information and working performance parameters includes at least one of the following: matching terrain attributes with robot mobility, wherein the mobility is based on the drive motor torque parameters and the structural type parameters of the mobile components of the autonomous robot; matching functional attributes with robot operational capabilities, wherein the operational capabilities are based on the working component type parameters and operational accuracy parameters of the autonomous robot; and matching environmental attributes with robot adaptability, wherein the adaptability is based on the sensor type parameters and detection accuracy parameters of the autonomous robot.

[0159] In some embodiments, configuring corresponding autonomous robots for sub-regions with different attributes according to the mapping relationship further includes: assessing the task complexity of the work area and determining the required robot type and / or number based on the task complexity; when the capabilities of a single robot do not meet the requirements of the sub-region, configuring multiple robots with complementary capabilities to work collaboratively.

[0160] In some embodiments, switching rules for the robot between different sub-regions are established, including at least one of switching conditions, switching paths, and cutting parameter configurations.

[0161] In some embodiments, purchase recommendations for autonomous robots are generated based on attribute information, including the type and quantity of autonomous robots.

[0162] Using the above method, an accurate and comprehensive map can be obtained quickly, thereby enabling complete work in the work area.

[0163] Referring to Figure 1, the aerial photography equipment 10 is equipped with an imaging sensor 101 (in other locations in this application, the imaging sensor 101 can be referred to as an image acquisition sensor), a first locator 102 (in other locations in this application, the first locator 102 can be referred to as a satellite positioning sensor), and a first controller 103. The imaging sensor 101 is configured to capture images of the working area; the first locator 102 is configured to acquire the coordinate information of the aerial photography equipment 10; the first controller 103 is configured to acquire the images and coordinate information of the working area, and generate a three-dimensional map of the working area, the three-dimensional map including the coordinate information of the working area. The coordinate information of the working area includes the longitude and latitude of any point within the working area. In some embodiments, the coordinate information may also include the altitude of any point within the working area.

[0164] In one embodiment, during the operation of the aerial photography equipment 10, the imaging sensor 101 is configured to capture multiple two-dimensional images of the work area from different directions of the work area at a preset aerial photography angle, and the first controller 103 is configured to generate a three-dimensional map of the work area based on the multiple two-dimensional images.

[0165] In one embodiment, the aerial photography device 10 can fly and collect images of the target area in the following manner. This flight method or image collection method can exist independently or can be combined with the flight method or image collection method of other embodiments.

[0166] As an example, the preset aerial photography angle is set to 45°, meaning the angle between the camera of the aerial photography device 10 and the horizontal direction is 45°. The aerial photography device 10 traverses the work area from the east, south, west, and north directions, capturing multiple two-dimensional images of the work area during each traversal. Of course, this embodiment does not limit the preset angle setting or the traversal direction of the work area; the preset aerial photography angle can be arbitrarily selected between 0° and 90°. To improve the shooting effect, the preset aerial photography angle can be arbitrarily selected between 30° and 60°, such as 30°, 40°, 45°, 50°, 60°, etc. The setting of the traversal direction of the work area by the aerial photography device 10 can be entirely based on the user's choice. It should be noted that in this embodiment, the aerial photography device 10 traversing the work area does not mean that the flight path of the aerial photography device 10 completely covers the entire work area, but rather that the two-dimensional images captured by the imaging sensor 101 can cover the entire work area.

[0167] In another embodiment, the aerial photography device 10 needs to select a flight area before operation, and control the aerial photography device 10 to fly and operate within the selected flight area. Specifically, a target area is defined on an existing map, and the target area includes the work area; the aerial photography device 10 can identify the target area, and the imaging sensor 101 of the aerial photography device 10 is configured to capture two-dimensional images of the target area from different directions at a preset aerial angle; a three-dimensional map of the target area is generated based on the two-dimensional images of the target area. Existing maps include, for example, Google Maps, Gaode Maps, Baidu Maps, etc. The user defines the target area on the existing map, and the target area completely covers the work area. The aerial photography device 10 can fly based on the user-defined target area and capture two-dimensional images of the entire target area from different directions, including the complete two-dimensional image of the work area.

[0168] As another example, the preset aerial photography angle is set to 45°, meaning the angle between the camera of the aerial photography device 10 and the horizontal direction is 45°. The aerial photography device 10 traverses the target area from the east, south, west, and north directions, capturing multiple two-dimensional images of the target area during each traversal. Of course, this embodiment does not limit the setting of the preset angle or the direction from which the target area is traversed. The preset aerial photography angle can be arbitrarily selected between 0° and 90°. To improve the shooting effect, the preset aerial photography angle can be arbitrarily selected between 30° and 60°, such as 30°, 40°, 45°, 50°, 60°, etc. The setting of the direction from which the aerial photography device 10 traverses the target area can be entirely based on the user's choice. It should be noted that in this embodiment, the aerial photography device 10 traversing the target area does not mean that the flight trajectory of the aerial photography device 10 completely covers the entire target area, but rather that the two-dimensional images captured by the imaging sensor 101 can cover the entire target area.

[0169] In this embodiment, the aerial photography equipment 10 can also plan the flight path and control the nodes captured by the imaging sensor 101 before operation, so as to ensure that the images captured by the imaging sensor 101 can cover the entire target area.

[0170] Specifically, the aerial photography device 10 is configured to begin shooting at a preset distance or preset time before entering the target area. The aerial photography device 10 is also configured to fly along a preset flight path while simultaneously capturing images of the target area. With the area directly above the target area as a reference, the flight path covers at least one side of the relative boundaries of the target area. It is understood that the target area has closed boundaries. The aerial photography device 10 flies within these closed boundaries. Since the angle of the imaging sensor 101 is not perpendicular to the target area but forms an angle with it, the imaging sensor 101 (or image acquisition sensor) can already capture a two-dimensional image of the target area before entering its upper boundary. In other words, the imaging sensor 101 can capture a two-dimensional image of the target area before the aerial photography device 10 reaches the upper boundary of one side of the target area. If shooting only begins when the aerial photography device 10 is directly above the upper boundary of one side of the target area, part of the target area will be missed. Therefore, it is necessary to start shooting in advance to avoid the imaging sensor 101 missing parts of the target area. The aforementioned preset distance or preset time is related to the preset aerial angle of the imaging sensor 101 and the flight speed of the aerial photography device 10. These settings can be manually configured, and this embodiment does not impose any restrictions. It is sufficient that the two-dimensional image captured by the imaging sensor 101 completely covers the entire target area. Similarly, since the imaging sensor 101 is at a certain angle to the target area, the two-dimensional image captured by the imaging sensor 101 can completely cover the entire target area before the aerial photography device 10 flies out of the target area. In other words, before the aerial photography device 10 reaches the other boundary of the target area, the imaging sensor 101 has already captured a complete two-dimensional image of the target area. To reduce the flight (working) time of the aerial photography device 10, it can be made to start flying in the opposite direction at a preset distance or preset time before leaving the target area. The aforementioned preset distance or preset time is related to the preset aerial angle of the imaging sensor 101 and the flight speed of the aerial photography device 10. These settings can be manually configured, and this embodiment does not impose any restrictions. It is sufficient that the two-dimensional image captured by the imaging sensor 101 completely covers the entire target area. In some embodiments, the preset distance or preset time for the aerial photography device 10 to begin shooting before reaching the target area is the same as the preset distance or preset time for the aerial photography device 10 to fly in the opposite direction before leaving the target area. In the above embodiments, the preset flight trajectory of the aerial photography device 10 can be a bow-shaped route or a zigzag route, etc.

[0171] In one embodiment of this application, a map of the target area can be generated in the manner described below, or in other ways as described above. This application does not limit the scope of the map generation.

[0172] In a further embodiment, the first controller 103 is configured to generate a three-dimensional map of the target area based on two-dimensional images of the target area. The imaging sensor 101 captures multiple two-dimensional images of the working area and transmits them to the first controller 103. Simultaneously, the first locator 102 acquires the positioning information of the aerial photography device 10 in real time and transmits the positioning information to the first controller 103. The first controller 103 fuses the multiple two-dimensional images with the positioning information to obtain a set of two-dimensional images containing the positioning information. There are various ways to combine the above two-dimensional images into a three-dimensional map, and this embodiment is not limited to any particular method. As an example, the first controller 103 can use a motion recovery structure combined with the SFM algorithm to generate a three-dimensional map from the set of two-dimensional images containing positioning information. It should be noted that the aerial photography device can generate a three-dimensional map online in real time, or it can export the two-dimensional image set offline and then have other devices process the two-dimensional image set to generate a three-dimensional map. The imaging sensor 101 can be a commonly used camera in the industry, while the first locator 102 can be an RTK locator. The RTK locator uses RTK differential information from a wireless receiving base station to achieve accurate positioning.

[0173] Furthermore, the aerial photography device 10 is also equipped with a first communication unit 104 for transmitting the aforementioned 3D map to the map generation device 20. The processing functions in the map generation device 20 are similar to those of the data processing system described in other sections. The first communication unit 104 is used to establish a communication connection between the aerial photography device 10 and the map generation device 20 via a network, and to send and receive data through the network, which includes wired and wireless communication networks. For example, the aerial photography device 10 can transmit the complete and valid 3D map to the map generation device 20 through the first communication unit 104, so that a user can view the 3D image at the map generation device 20.

[0174] The imaging sensor 101, the first locator 102, the first controller 103, and the first communication unit 104 described above are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, the imaging sensor 101, the first locator 102, the first communication unit 104, and the first controller 103 can be electrically connected through one or more communication buses or signal lines.

[0175] In one embodiment of this application, the boundary of the target area map or components such as charging stations can be determined in the manner described below, or other methods described above can be used, and this application does not limit this method.

[0176] Please continue to refer to Figure 1. The map generation device 20 includes a second controller 203, which is configured to acquire the above-mentioned three-dimensional map and generate a work area map that can be recognized by the autonomous working machine based on the three-dimensional map. The work area map includes at least the boundary of the work area. The autonomous working machine moves and / or works in the work area based on the work area map.

[0177] Specifically, the map generation device 20 further includes a second communication unit 204, which is used to acquire a 3D map from the aerial photography device 10. In other words, the second communication unit 204 is used to communicate with the first communication unit 104 to obtain the 3D map. In one embodiment, the second communication unit 204 can communicate directly with the first communication unit 104, and the map generation device 20 directly acquires the 3D map from the aerial photography device 10. In other embodiments, the aerial photography device 10 transmits the 3D map to a server or cloud through the first communication unit 104, and the map generation device 20 acquires the 3D map from the server or cloud through the second communication unit 204. The mutual transmission of data between the first communication unit 104, the second communication unit 204, and the server or cloud can employ wired data transmission modules (such as cables, optical fibers) or wireless transmission modules (such as Bluetooth, cellular mobile networks, Wi-Fi local area networks, etc.) in the prior art, and this disclosure does not impose any limitations.

[0178] In a further embodiment, the map generation device 20 can be a user-operable device that interacts with the user, such as a mobile phone, computer, tablet, etc. The 3D map is transmitted to the user-operable device via information exchange between the first communication unit 104 and the second communication unit 204. The user-operable device is configured to provide the user with an interface for operating the 3D map. The map generation device 20 is configured to generate the work area map based on the user's operations on the 3D map.

[0179] Specifically, the map generation device 20 (i.e., the user-operable device) is also equipped with a display 201 and an input unit 202. The display 201 is used to display the 3D map acquired from the aerial photography device 10, as well as the user interface for operating the 3D map. The input unit 202 is used by the user to operate the 3D map. The second controller 203 receives the input signal transmitted by the input unit and generates a working area map that can be recognized by the self-moving device.

[0180] It should be noted that the work area map here is a two-dimensional map carrying coordinate information. The user can observe the entire terrain of the work area through the three-dimensional map displayed on monitor 201, including the boundaries of the work area (e.g., for an automatic lawnmower, the boundary is the dividing line between grass and non-grass areas), inaccessible areas within the work area (e.g., for an automatic lawnmower, flower beds and ponds are inaccessible areas), passageways connecting two sub-work areas (passages that the autonomous machine needs to traverse when moving from one sub-work area to another), narrow passageways, charging stations for the autonomous machines located within the work area, trees, steep slopes, potholes, etc. One particularly noteworthy terrain feature is the presence of obstructions in the work area, such as trees or eaves. Signals received by the locator under these obstructions may be blocked; we refer to these areas as shadow areas. However, the positioning signal of the aerial photography device 10 is not blocked by these obstructions; therefore, the three-dimensional map acquired by the aerial photography device 10 does not contain shadow areas and can comprehensively display the terrain features of the work area.

[0181] Specifically, the display 201 is configured to show the 3D map to the user, the input unit 202 is configured to allow the user to select at least three boundary points in the 3D map, and the second controller 203 of the map generation device 20 (i.e., the user-operable device) is configured to automatically generate the boundaries of the work area map based on the at least three boundary points selected by the user. The user can input more boundary points into the input unit 202, such as 5, 7, 10, 20, 30, 50, etc. This embodiment does not limit the number of boundary points that the input unit 202 can input. The more boundary points input into the input unit 202, the more effective information the map generation device 20 obtains, and the more accurate and realistic the generated boundaries become. When the map generation device 20 receives the boundary point information input by the user, it can automatically generate the boundaries of the work area map that the autonomous working machine can recognize through its built-in algorithm. Of course, the input unit 202 can also be configured to allow the user to delineate the boundaries of the work area with lines. That is, the user can directly draw the boundaries of the target area through the input unit 202.

[0182] Taking a touchscreen phone as an example, the map generation device 20 is the touchscreen of the phone, and the input unit 202 is also the touchscreen of the phone. The user can observe the boundary of the target area in the 3D map on the touchscreen and then select at least three or more boundary points. The touchscreen phone can then automatically generate the boundary of the working area map that the autonomous machine can recognize through its built-in algorithm. Alternatively, when the user observes the boundary of the target area in the 3D map on the touchscreen, they can directly draw lines along the boundary of the target area to delineate the complete boundary. When the autonomous machine is an automatic lawnmower, the working area map that the automatic lawnmower can recognize is a PIM map.

[0183] Furthermore, the input unit 202 is configured to allow the user to define accessible or inaccessible areas on the 3D map, and the map generation device 20 is configured to generate accessible or inaccessible areas for the autonomous machine in the work area map based on the accessible or inaccessible areas defined by the user. The user can input areas that the autonomous machine cannot enter in the input unit 202; inaccessible areas include, for example, flower beds, swings, toy facilities, etc.

[0184] Regarding the method by which the user inputs the inaccessible area into the input unit 202, the above-described embodiment of inputting boundaries can be referenced. The input unit 202 is configured to allow the user to input multiple boundary points surrounding the inaccessible area, such as 3, 5, 7, 10, 20, 30, 50, etc. This embodiment does not limit the number of points surrounding the inaccessible area that the input unit 202 can input. The more points input into the input unit 202, the more effective information the map generation device 20 obtains, and the more accurate and realistic the generated boundary surrounding the inaccessible area becomes. When the second controller 203 of the map generation device 20 receives the information of the boundary points surrounding the inaccessible area input by the user, it can automatically generate the inaccessible area in the working area map that can be recognized by the autonomous working machine through the built-in algorithm program. Of course, the input unit 202 can also be configured to allow the user to delineate the inaccessible area in the working area with lines. That is, the user can directly draw the boundary of the inaccessible area through the input unit 202.

[0185] Taking a touchscreen phone as an example, the map generation device 20 is the touchscreen of the phone, and the input unit 202 is also the touchscreen of the phone. The user can observe areas inaccessible to the autonomous robot in the 3D map on the touchscreen. Then, by selecting at least three boundary points (or more) around these inaccessible areas on the touchscreen, the phone can automatically generate a map of the inaccessible areas in the work area that the autonomous robot can recognize, using its built-in algorithm. Alternatively, when the user observes an inaccessible area in the 3D map on the touchscreen, they can directly draw lines along the boundary of the inaccessible area to delineate the entire inaccessible region. The autonomous robot will not enter these inaccessible areas when moving and / or working based on this work area map.

[0186] Using the same method as described above for generating inaccessible areas, the user can input the areas that the autonomous robot can enter into the input unit 202. The map generation device 20 then automatically generates an accessible area in the work area map that the autonomous robot can recognize, based on its built-in algorithm. The autonomous robot then enters these accessible areas when moving and / or working based on this work area map.

[0187] Furthermore, the input unit 202 is also configured to allow the user to define channels in the 3D map, and the map generation device 20 is configured to generate channels in the work area map based on the channels defined by the user. The input unit 202 can allow the user to input channel information, such as marking the location and / or shape of the channels in the 3D map. It is understood that the work area may not be a single area, but rather a combination of multiple sub-areas; the connections between these sub-areas are referred to as channels.

[0188] The method by which the input unit 202 provides the user with the input channel can be referenced in the above embodiment. The input unit 202 is configured to allow the user to input multiple boundary points around the channel, such as 3, 5, 7, 10, 20, 30, 50, etc. This embodiment does not limit the number of points around the channel that the input unit 202 can input. The more points input into the input unit 202, the more effective information the map generation device 20 obtains, and the more accurate and realistic the generated boundary around the channel becomes. When the map generation device 20 receives the information of the boundary points around the channel input by the user, it can automatically generate the channel in the work area map that can be recognized by the autonomous working machine through the built-in algorithm program. Of course, the input unit 202 can also be configured to allow the user to draw the channel in the work area with lines, that is, the user can directly draw the boundary of the channel through the input unit 202. Or the user can directly mark the direction, start point, and end point of the channel through the input unit 202.

[0189] Taking a touchscreen phone as an example, the map generation device 20 is the touchscreen of the phone, the display 201 is the touchscreen of the phone, and the input unit 202 is also the touchscreen of the phone. Users can observe channels in the 3D map on the touchscreen and then select at least three or more boundary points around the channels. The touchscreen phone can then automatically generate a map of the working area that can be recognized by the autonomous machine using its built-in algorithm. Alternatively, when users observe channels in the 3D map on the touchscreen, they can directly draw lines along the boundaries of the channels to circle the complete channels.

[0190] Furthermore, the input unit 202 is also configured to allow the user to delineate charging stations on a 3D map, and the map generation device 20 is configured to generate a map of charging stations in the work area based on the user-delineated charging stations. The input unit 202 allows the user to input information about the charging stations, such as the length and width of the charging stations and / or to mark the location of the charging stations on the 3D map.

[0191] Regarding the method by which the input unit 202 provides the user with input of charging stations, the above embodiment can be referenced. The input unit 202 is configured to allow the user to input multiple boundary points surrounding the charging station, such as 3, 5, 7, 10, 20, 30, 50, etc. This embodiment does not limit the number of points surrounding the charging station that the input unit 202 can input. The more points input to the input unit 202, the more effective information the map generation device 20 obtains, and the more accurate and realistic the generated boundary around the charging station becomes. When the map generation device 20 receives the information of the boundary points surrounding the charging station input by the user, it can automatically generate a map of the working area that the autonomous working machine can recognize through its built-in algorithm. Of course, the input unit 202 can also be configured to allow the user to delineate the charging stations in the working area with lines, that is, the user can directly draw the boundary of the charging station through the input unit 202. Or the user can directly mark the location of the charging station through the input unit 202.

[0192] Taking a touchscreen phone as an example, the map generation device 20 is the touchscreen of the phone, the display 201 is the touchscreen of the phone, and the input unit 202 is also the touchscreen of the phone. Users can observe charging stations in a 3D map on the touchscreen and then select at least three or more boundary points around the charging station. The touchscreen phone, through its built-in algorithm, can automatically generate a map of the charging stations in the working area that can be recognized by the autonomous machine. Alternatively, when users observe charging stations in a 3D map on the touchscreen, they can directly draw lines along the boundaries of the charging stations to circle the complete charging station. Or, when users observe charging stations in a 3D map on the touchscreen, they can mark the location of the charging stations.

[0193] In another embodiment, the map generation device 20 is configured to automatically or semi-automatically generate a work area map based on the aforementioned 3D map. It should be noted that the work area map here is a 2D map carrying coordinate information. In this embodiment, the map generation device 20 automatically identifies the boundaries of the work area in the 3D map using a built-in algorithm, and then automatically generates the boundaries of the work area map that can be recognized by the autonomous working machine. In this embodiment, the map generation device 20 includes a display 201, which is configured to display the 3D map and the boundaries of the work area map automatically generated by the map generation device 20. It should also be noted that configuring the map generation device 20 to semi-automatically generate the work area map based on the aforementioned 3D map means that after the map generation device 20 automatically generates the boundaries of the work area map that can be recognized by the autonomous working machine, the boundaries of the work area map can be corrected through manual operation by the user.

[0194] Furthermore, the map generation device 20 (i.e., a user-operable device) also includes an input unit 202, which is configured to allow the user to manipulate the boundaries of the work area map to correct the boundaries of the work area map. The boundaries of the work area map are transmitted to (or displayed on) the user-operable device, which is configured to provide the user with an interface for manipulating the work area map; the boundaries of the work area map are corrected based on the user's manipulation of the boundaries of the work area map on the input unit 202.

[0195] Taking a touchscreen phone as an example, the map generation device 20 includes both the display 201 and the input unit 202. Users can view a 3D map and the boundaries of the work area map automatically generated by the phone's built-in algorithm on the touchscreen. If the user observes errors in the boundaries of the automatically generated work area map, they can modify them using the touchscreen. For example, they can drag the boundary lines to make the boundaries of the work area map more accurate.

[0196] Furthermore, in this embodiment, the 3D map also includes inaccessible areas, passageways, and charging stations. The map generation device 20 can automatically identify at least one of the inaccessible areas, passageways, and charging stations, and generate inaccessible areas, passageways, and charging stations in the work area map. The display 201 is configured to display the 3D map and at least one of the inaccessible areas, passageways, and charging stations in the work area map automatically generated by the map generation device 20. The input unit 202 is configured to allow the user to operate on the inaccessible areas, passageways, and charging stations in the work area map to correct the inaccessible areas, passageways, and charging stations in the work area map.

[0197] The method for users to correct inaccessible areas, passages, and charging stations in the work area can refer to the method for users to correct the boundaries of the work area in the above embodiments, or the method for users to independently calibrate inaccessible areas, passages, and charging stations, which will not be elaborated here.

[0198] In some embodiments, the map generation device 20 is further configured to automatically or through user operation mark at least one of the information of shaded areas, slope areas, and pothole areas in the 3D map onto the working area map. The information of the shaded areas includes at least the location and / or shape of the shaded areas, the information of the slope areas includes at least the location and slope of the slope areas, and the information of the pothole areas includes at least the location and / or depth of the pothole areas. It should be noted that the aerial surveying technology of the aerial photography equipment 10 is already very mature, and the generation of information of shaded areas, slope areas, and pothole areas in the 3D map can be achieved through existing technologies, which will not be elaborated upon in this disclosure. As for converting the information of shaded areas, slope areas, and pothole areas in the 3D map into the information of shaded areas, slope areas, and pothole areas in the working area map, it can be done automatically by the map generation device 20, or it can be done by the user marking the area on the 3D map and then the map generation device 20 generating the information based on the user's marking. For details on how to generate a working area map that can be recognized by an autonomous machine from the shaded areas, slope areas, and pothole areas in the 3D map, please refer to the above-mentioned embodiments, which will not be repeated here.

[0199] In some embodiments, after a work area map is generated by the map generation device 20 or by a user-operable device, the work area map needs to be transmitted to an autonomous working machine. The autonomous working machine is configured to obtain a recognizable work area map from the user-operable device. Alternatively, the user-operable device transmits the work area map to a server or cloud, and the autonomous working machine is configured to obtain a recognizable work area map from the server or cloud.

[0200] The autonomous working machine is equipped with a locator and relies on the locator to obtain its own location in real time. Then, it autonomously performs work tasks within the work area based on a work area map. For example, the autonomous working machine can pre-plan a movement path based on the work area map and move and work along that path. This movement path can be a bow-shaped path or a U-shaped path.

[0201] In one embodiment of this application, when an autonomous robot with satellite positioning function moves to a shaded area, it can move in the following manner.

[0202] Autonomous machines will lose their positioning signal if they remain in shaded areas for extended periods, leading to positioning errors. Because shaded areas are marked on the work area map, the autonomous machine can identify the location and shape of these areas. When moving into a shaded area, the machine can be controlled to accelerate its movement and quickly leave. Alternatively, the movement path can be altered to intermittently enter and exit the shaded area. Specifically, when the autonomous machine moves in a zigzag pattern, it can repeatedly enter and exit the shaded area. This prevents the machine from losing its positioning signal due to prolonged exposure to shaded areas.

[0203] In one embodiment of this application, when an autonomous robot without strong driving capability moves to a sloping or potholed area, it can move in the following manner.

[0204] The autonomous machine can identify the location and slope of the slope area through the work area map, and then control the autonomous machine to move in a direction roughly perpendicular to the slope direction. This avoids the problem of the autonomous machine losing speed when moving along the slope direction and losing work efficiency during uphill and downhill movements.

[0205] Autonomous machines can identify the location of potholes by using a map of their work area, thereby avoiding those potholes and preventing themselves from getting stuck in them.

[0206] Each module in the aforementioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0207] Based on the same inventive concept, this disclosure also provides a method for mapping a work area, in which an autonomous machine can move and / or work, as shown in Figure 2. The method includes:

[0208] S1: Obtain a 3D map of the work area using aerial photography equipment 10. The 3D map includes the coordinate information of the work area.

[0209] S2: Generate a work area map that the autonomous machine can recognize based on the 3D map. The work area map includes at least the boundaries of the work area; the autonomous machine moves and / or works in the work area based on the work area map.

[0210] Please refer to Figure 3. In some embodiments, the method for acquiring a 3D map of the work area using aerial photography equipment 10 includes:

[0211] S11: Control the aerial photography equipment 10 to capture two-dimensional images of the work area from different directions at preset aerial photography angles.

[0212] S12: Generate a 3D map of the working area based on the 2D image of the target area.

[0213] It should be noted that the implementation methods of the aerial photography equipment 10 in taking two-dimensional images of the work area from different directions of the work area at preset aerial photography angles, and the implementation methods in generating a three-dimensional map of the work area from the two-dimensional images of the work area, have been described in detail in the above-mentioned embodiments of the mapping system 100, and will not be repeated here.

[0214] Please refer to Figures 4 and 5. In another embodiment, the method for acquiring a 3D map of the work area using aerial photography equipment 10 includes:

[0215] S13: Define the target area on the existing map. The target area includes the work area.

[0216] S14: Control the aerial photography equipment 10 to capture two-dimensional images of the target area from different directions at preset aerial photography angles.

[0217] S15: Generate a three-dimensional map of the target area based on the two-dimensional image of the target area.

[0218] The aerial photography equipment 10 is controlled to capture two-dimensional images of the target area from different directions at preset aerial photography angles, including:

[0219] S140: Control the aerial photography equipment 10 to start shooting at a preset distance or preset time before entering the target area, control the aerial photography equipment 10 to fly along a preset flight path, and capture images of the target area, with the top of the target area as a reference, and the flight path at least covers at least one side of the relative boundary of the target area.

[0220] It should be noted that the methods for delineating target areas in existing maps, controlling aerial photography equipment 10 to capture two-dimensional images of the target area from different directions at preset aerial photography angles, and generating three-dimensional maps of the target area based on the two-dimensional images of the target area have been described in detail in the embodiments of the mapping system 100 above, and will not be repeated here.

[0221] Please refer to Figure 6. In some embodiments, the above mapping method further includes:

[0222] S3: Transmit the 3D map to a user-operable device that provides the user with an interface to manipulate the 3D map.

[0223] Generate a work area map that can be recognized by the autonomous working machine based on a 3D map, including:

[0224] S20: Generate a work area map based on the user's operations on the 3D map.

[0225] Generating a work area map based on user interactions with a 3D map includes at least one of the following steps:

[0226] S201: Generate the boundaries of the work area map based on at least three boundary points in the 3D map selected by the user on the interface.

[0227] S202: Based on the areas that can or cannot be entered in the 3D map defined by the user on the interface, generate the areas that autonomous work machines can or cannot enter in the work area map.

[0228] S203: Generate channels in the work area map based on the channels marked by the user in the 3D map on the interface.

[0229] S204: Based on the charging stations marked by the user on the interface in the 3D map, generate the charging stations in the work area map.

[0230] The above-mentioned mapping methods may also include:

[0231] S205: Automatically or through user operation, at least one of the information of the shaded area, the information of the slope area, and the information of the pothole area in the three-dimensional map is marked in the working area map. The information of the shaded area includes at least the location and / or shape of the shaded area, the information of the slope area includes at least the location and / or slope of the slope area, and the information of the pothole area includes at least the location of the pothole area.

[0232] It should be noted that the following methods have been described in detail in the embodiments of the mapping system 100: generating the boundaries of the work area map based on at least three boundary points selected by the user on the interface; generating areas in the work area map that the autonomous working machine can or cannot enter based on areas in the 3D map that the user delineates on the interface; generating passages in the work area map based on passages marked by the user on the interface; generating charging stations in the work area map based on charging stations marked by the user on the interface; and automatically or through user operation marking at least one of the information of shaded areas, slope areas, and pothole areas in the 3D map onto the work area map. These methods will not be repeated here.

[0233] In another embodiment, generating a work area map recognizable by the autonomous working machine based on a 3D map includes:

[0234] S21: Automatically identify the boundaries of the work area based on the 3D map and generate the boundaries of the work area map.

[0235] S22: Transmit the boundaries of the work area map to a user-operable device configured to provide the user with an interface for manipulating the work area map.

[0236] S23: Correct the boundaries of the work area map based on the user's operations on the boundaries of the work area map.

[0237] In this embodiment, the boundaries of the work area map can be automatically generated based on a 3D map without manual intervention, making mapping more intelligent and convenient. It should be noted that the methods for automatically identifying the boundaries of the work area based on a 3D map and generating the boundaries of the work area map, the methods for transmitting the boundaries of the work area map to a user-operable device, and the methods for correcting the boundaries of the work area map based on user operations on the boundaries of the work area map have been described in detail in the embodiments of the mapping system 100 above, and will not be repeated here.

[0238] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the accompanying drawings may include multiple steps or stages, which are not necessarily completed at the same time, but may be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but may be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0239] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The terms “and / or,” “and / or,” and “at least one of” as used herein include any and all combinations of one or more of the associated listed items.

[0240] The technical features of the above embodiments can also be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0241] The embodiments described above merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A control method of an autonomous work system, wherein, The method comprises: acquiring environmental information collected above the target area, the environmental information comprising image data and position data; generating a map of the target area based on the environmental information, wherein the map comprises at least one attribute information associated with a specific area in the map; generating a working strategy of the autonomous robot in the target area based on the attribute information.

2. The method of any claim, wherein, The image data comprises at least one of orthographic images, oblique images, and close-range images.

3. The method of any claim, wherein, The method comprises georeferencing the image information based on the position information to generate a map of the target area.

4. The method of any claim, wherein, The method comprises format conversion and / or coordinate calibration of the map of the target area to generate a map matching the navigation system of the autonomous robot.

5. The method of any claim, wherein, The attribute information comprises at least one of terrain features, environmental features, and functional features.

6. The method of any claim, wherein, The attribute information further comprises at least one of terrain feature classification, environmental feature classification, and functional feature classification.

7. The method of any claim, wherein, The environmental type comprises a satellite signal shielding state, and the method comprises: processing the image information to identify obstacles affecting the quality of satellite positioning signals; calculating the shielding range of the obstacles according to at least one of the position, height, shape parameters, and distribution density of the obstacles; determining a working area where the quality of satellite positioning signals is less than a preset signal quality threshold based on the shielding range.

8. The method according to any one of the preceding claims, wherein According to the attribute information, the target area is divided into a plurality of sub-areas, each of which comprises at least one attribute information.

9. The method of any claim, wherein, The method of generating a working strategy of the autonomous robot in the plurality of working areas based on the attribute information further comprises: establishing a mapping relationship between attribute information and working strategies; configuring corresponding working strategies for sub-areas with different attributes according to the mapping relationship.

10. The method of any claim, wherein, The method of generating a working strategy of the autonomous robot in the plurality of sub-areas based on the attribute information further comprises: acquiring working performance parameters of the autonomous robot, including types and / or capabilities; establishing a mapping relationship between attribute information and the working performance parameters; configuring corresponding autonomous robots for sub-areas with different attributes according to the mapping relationship.

11. The method of any claim, wherein, The establishment of the mapping relationship between attribute information and the working performance parameters comprises at least one of: matching terrain attributes with robot movement capabilities, the movement capabilities being based on driving motor torque parameters and structure type parameters of movement components of the autonomous robot; matching functional attributes with robot work capabilities, the work capabilities being based on work component type parameters and work precision parameters of the autonomous robot; matching environmental attributes with robot adaptability, the adaptability being based on sensor type parameters and detection precision parameters of the autonomous robot.

12. The method of any claim, wherein, The configuration of corresponding autonomous robots for sub-areas with different attributes according to the mapping relationship further comprises: evaluating the task complexity of the working area and determining the required types and / or quantities of robots based on the task complexity; when the capabilities of a single robot do not meet the requirements of a sub-area, configuring multiple robots with complementary capabilities to work collaboratively.

13. The method of any claim, wherein, The method comprises: establishing switching rules of the robot between different sub-regions, including at least one of switching conditions, switching paths and cutting parameter configurations.

14. The method of any claim, wherein, The method comprises: generating a purchase suggestion of the autonomous robot according to the attribute information, the purchase suggestion comprising a type and a quantity of the autonomous robot.

15. A map acquisition method, wherein, Comprise: Obtaining environmental information collected above the target area, the environmental information comprising image data, position data; Generating a map of the target area based on the environmental information, wherein the map contains at least one attribute information, and the attribute information is associated with a specific region in the map.

16. The method of any claim, wherein, The image data includes at least one of orthographic images, oblique images and close-range images.

17. The method of any claim, wherein, Based on the position information, the image information is geographically registered to generate a map of the target area.

18. The method of any claim, wherein, The method comprises: format conversion and / or coordinate calibration of the map of the target area to generate a map matching the autonomous robot navigation system.

19. The method of any claim, wherein, The attribute information includes at least one of terrain features, environmental features and functional features.

20. The method of any claim, wherein, The attribute information further comprises at least one of the terrain feature classification, environmental feature classification and functional feature classification.

21. The method of any claim, wherein, The environment type includes a satellite signal shielding state, and the method comprises: Processing the image information to identify obstacles affecting the quality of satellite positioning signals; According to at least one of the position, height, shape parameters and distribution density of the obstacle, the shielding range of the obstacle is calculated; Based on the shielding range, determine the working area where the satellite positioning signal quality is less than the preset signal quality threshold.

22. The method of any claim, wherein, According to the attribute information, the target area is divided into a plurality of sub-regions, and each of the plurality of sub-regions comprises at least one attribute information.

23. A control method of an autonomous robot, comprising: Obtaining a map of a target area, the map comprising a plurality of sub-regions, each of the plurality of sub-regions comprising at least one attribute information; Establishing a mapping relationship between the attribute information and the working strategy; According to the mapping relationship, configure corresponding working strategies for sub-regions with different attributes.

24. The method of any claim, wherein, Generating working strategies of autonomous robots in the plurality of sub-regions based on the attribute information further comprises: Obtaining working performance parameters of autonomous robots, the working performance parameters comprising types and / or capabilities; Establishing a mapping relationship between the attribute information and the working performance parameters; According to the mapping relationship, configure corresponding autonomous robots for sub-regions with different attributes.

25. The method of any claim, wherein, The establishment of the mapping relationship between the attribute information and the working performance parameters comprises at least one of: Matching terrain attributes with robot movement capabilities, the movement capabilities based on drive motor torque parameters and structure type parameters of the autonomous robot; Matching functional attributes with robot work capabilities, the work capabilities based on work component type parameters and work precision parameters of the autonomous robot; Matching environmental attributes with robot adaptability, the adaptability based on sensor type parameters and detection precision parameters of the autonomous robot.

26. The method of any claim, wherein, The configuring of the respective autonomous robots for the sub-regions with different attributes according to the mapping relationship further includes: evaluating the task complexity of the working area, and determining the required robot type and / or quantity based on the task complexity; when the single robot capability does not meet the sub-region requirements, configuring multiple robots with complementary capabilities to work collaboratively.

27. The method of any claim, wherein, The method includes: establishing switching rules of the robots between different sub-regions, including at least one of switching conditions, switching paths and cutting parameter configurations.

28. The method of any claim, wherein, The method includes: generating a purchase suggestion of the autonomous robot according to the attribute information, the purchase suggestion including the type and quantity of the autonomous robot.

29. An autonomous work system, wherein, The autonomous working system includes: a data processing system configured to obtain environment information collected in the air above the target area, the environment information including image information and position information; generate a map of the target area based on the environment information; wherein the map includes at least one attribute information, and the attribute information is associated with a specific region in the map; a working strategy generation system configured to generate a working strategy of an autonomous robot in the target area based on the attribute information.

30. The system of any claim, wherein, The autonomous working system further includes: an autonomous flight device configured to collect environment information in the air above the target area through multiple sensors during flight in the target area.

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