A physical marker-based work area automatic construction method

Abstract

The application discloses a kind of physical marker-based work area automatic construction method, it is related to mobile robot autonomous work technical field, method includes: control robot is located in the multiple physical markers of the boundary of the work area to be done and is identified, obtains the spatial position information of each physical marker;The physical marker is used to limit the boundary position of the work area to be done;According to the spatial position information, the physical marker is sorted and connected, and the target work boundary is obtained.The application can be constructed without pre-built map or fixed boundary facility, control robot automatically identifies field physical marker and generates target work boundary based on spatial position information sorting connection, realizes the automatic quick construction of work area.

Description

Technical Field

[0001] This invention relates to the field of autonomous operation technology for mobile robots, and in particular to a method for automatically constructing a work area based on physical markers. Background Technology

[0002] In the stone flooring maintenance industry, mobile robots or semi-automatic equipment typically employ various technical solutions during actual operation. One solution is a work area planning method based on pre-built maps. This method requires a complete map of the work site in advance and is suitable for fixed environments. However, stone maintenance operations often occur in public places such as shopping malls, hotels, and airports, where the environment changes frequently, making it difficult to create stable maps in advance, thus limiting its practicality.

[0003] Another technical solution is to manually set the work area based on virtual fences or electronic maps. This method requires manual drawing of the work area boundaries on the terminal interface, which is complex, requires highly skilled operators, and carries a significant risk of misoperation on-site. In addition, work area demarcation based on fixed boundaries such as magnetic strips or cables also requires the pre-laying or installation of boundary facilities, resulting in high construction costs and making it unsuitable for the temporary and rapid deployment needs commonly encountered in stone maintenance operations.

[0004] In actual stone maintenance operations, on-site personnel commonly use physical markers such as cones or warning cones to isolate work areas. However, existing robotic systems typically cannot automatically identify these physical markers and construct work areas accordingly, still requiring manual intervention. All of the aforementioned existing technologies have their own limitations and cannot meet the actual needs of industries such as stone maintenance for rapid deployment and safe operation.

[0005] Therefore, how to enable mobile robots to quickly and reliably determine their work areas without the need for pre-built maps or fixed boundary facilities has become a pressing technical problem that needs to be solved. Summary of the Invention

[0006] The technical problem this invention aims to solve is to address the shortcomings of existing technologies, specifically the issue that robots cannot automatically identify physical landmarks on-site and construct work areas accordingly, leading to the need for manual intervention and low deployment efficiency. Specifically, this invention provides a method for automatically constructing work areas based on physical landmarks, as detailed below: 1) In a first aspect, the present invention provides a method for automatically constructing a work area based on physical markers, the specific technical solution of which is as follows: S1, control the robot to identify multiple physical markers located at the boundary of the work area, and obtain the spatial position information of each physical marker; the physical markers are used to define the boundary position of the work area. S2, based on the spatial location information, sort and connect the physical markers to obtain the target operation boundary.

[0007] The beneficial effects of the automatic construction method for work areas based on physical markers provided by this invention are as follows: Without the need for pre-built maps or fixed boundary facilities, the robot can automatically identify the physical markers already placed on site and obtain their spatial location information. Based on the spatial location information, the physical markers are sorted and connected to obtain the target operation boundary. This enables the direct use of commonly used physical markers on site and the automatic construction of operation boundaries, effectively reducing the risk of manual setting and misoperation, lowering additional hardware and deployment costs, and improving the automation level of robot operation area construction and rapid deployment capability in temporary operation scenarios.

[0008] Based on the above solution, the present invention can be further improved as follows.

[0009] Furthermore, the identification of multiple physical markers located at the boundary of the work area includes: The robot uses its environmental perception sensors to perform multi-sensor fusion recognition of the physical markers. The environmental perception sensors include a visual sensor and an optical ranging sensor.

[0010] Furthermore, the sorting and connecting of the physical markers specifically includes: By employing any one of the polar angle sorting strategy, convex hull algorithm, polygon fitting algorithm, or shortest closed loop generation algorithm, the physical markers are sorted and connected according to the spatial location information to obtain the target operation boundary.

[0011] Furthermore, after obtaining the target job boundary, the method further includes: performing a legality verification on the target job boundary; The legality verification includes at least one of the following: determining whether the target operation boundary is closed, determining whether the target operation boundary has self-intersection, determining whether the area enclosed by the target operation boundary is greater than a preset area threshold, and determining whether the distance between adjacent physical markers is within a preset distance range.

[0012] Furthermore, after obtaining the target operation boundary, the process also includes: The target work boundary is shifted inward by a preset safety distance to generate a safe work area.

[0013] Furthermore, after obtaining the target operation boundary, the process also includes: During the operation, the spatial position information of each physical marker is monitored in real time, and the displacement is calculated based on the spatial position information of each physical marker before and after the change. When the displacement exceeds a preset displacement threshold or the number of physical markers changes, repeat step S2 to update the target work boundary.

[0014] 2) In a second aspect, the present invention also provides an automatic construction system for work areas based on physical markers, the specific technical solution of which includes: an identification and positioning module and a sorting and connection module; The identification and positioning module is used to control the robot to identify multiple physical markers located at the boundary of the work area and obtain the spatial position information of each physical marker; the physical markers are used to define the boundary position of the work area. The sorting and connection module is used to sort and connect the physical markers according to the spatial location information to obtain the target operation boundary.

[0015] Based on the above solution, the present invention can be further improved as follows.

[0016] Furthermore, the identification of multiple physical markers located at the boundary of the work area includes: The robot uses its environmental perception sensors to perform multi-sensor fusion recognition of the physical markers. The environmental perception sensors include a visual sensor and an optical ranging sensor.

[0017] Furthermore, the sorting and connecting of the physical markers specifically includes: By employing any one of the polar angle sorting strategy, convex hull algorithm, polygon fitting algorithm, or shortest closed loop generation algorithm, the physical markers are sorted and connected according to the spatial location information to obtain the target operation boundary.

[0018] Furthermore, after obtaining the target job boundary, the method further includes: performing a legality verification on the target job boundary; The legality verification includes at least one of the following: determining whether the target operation boundary is closed, determining whether the target operation boundary has self-intersection, determining whether the area enclosed by the target operation boundary is greater than a preset area threshold, and determining whether the distance between adjacent physical markers is within a preset distance range.

[0019] Furthermore, after obtaining the target operation boundary, the process also includes: The target work boundary is shifted inward by a preset safety distance to generate a safe work area.

[0020] Furthermore, after obtaining the target operation boundary, the process also includes: During the operation, the spatial position information of each physical marker is monitored in real time, and the displacement is calculated based on the spatial position information of each physical marker before and after the change. When the displacement exceeds a preset displacement threshold or the number of physical markers changes, the sorting connection module is repeated to update the target operation boundary.

[0021] 3) In a third aspect, the present invention also provides a computer device, the computer device including a processor coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor to enable the computer device to implement any of the above methods.

[0022] 4) In a fourth aspect, the present invention also provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to enable a computer to implement any of the above methods.

[0023] It should be noted that the beneficial effects of the technical solutions of the second to fourth aspects of the present invention and their corresponding possible implementations can be found in the above description of the technical effects of the first aspect and its corresponding possible implementations, and will not be repeated here. Attached Figure Description

[0024] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating the steps of an automatic construction method for work areas based on physical markers according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0026] like Figure 1 As shown in the figure, an automatic construction method for work areas based on physical markers according to an embodiment of the present invention includes the following steps: S1, the robot is controlled to identify multiple physical markers located at the boundary of the work area and obtain the spatial position information of each physical marker; the physical markers are used to define the boundary position of the work area. The specific implementation is as follows: The robot uses onboard environmental sensors to detect and identify physical markers deployed on-site. A robot is an automated mechanical device capable of sensing its environment through sensors, making decisions and controlling its operation through a processor, and performing movement or manipulation tasks. Physical markers are vertical markers with predetermined shapes and height characteristics, such as cones or warning cones. Physical markers can also be replaced with other vertical markers with reflective features, visual coding, or height characteristics, used to create visual spatial constraint markings at the boundaries of the work area. After detecting physical markers, the robot acquires the spatial position information of each marker; specifically, this determines the spatial position of each marker within the robot's coordinate system or a unified coordinate system. The robot's coordinate system is a relative coordinate system established with the robot itself as the origin. A unified coordinate system is a coordinate system that transforms data from multiple sensors to the same reference system; conversion between the robot's coordinate system and the unified coordinate system can be achieved through coordinate transformation. Spatial position information includes the two-dimensional or three-dimensional coordinates of the physical markers, which characterize the specific location of the physical markers in the work environment.

[0027] In a preferred embodiment, the identification of multiple physical markers located at the boundary of the work area is specifically performed by: multi-sensor fusion identification of the physical markers using the robot's environmental perception sensors, including vision sensors and optical ranging sensors. The vision sensor can be a monocular or binocular camera, used to acquire environmental images containing the physical markers, and image recognition algorithms are used to detect the pixel positions of the physical markers in the environmental images. The optical ranging sensor is a sensor that uses optical principles to measure the distance to objects, including lidar or laser displacement sensors. The optical ranging sensor directly obtains the distance information of the physical marker surface by emitting a light beam and receiving the reflected signal. Multi-sensor fusion identification involves synchronizing and spatially aligning the image coordinates of the physical markers detected by the vision sensors with the distance information detected by the optical ranging sensors. Through coordinate transformation and data fusion algorithms, more accurate spatial position information of each physical marker is calculated. Specifically, the identification results are verified by extracting the geometric topological features and reflectivity features of the physical markers to improve the robustness of identification under complex lighting or partial occlusion conditions. Among them, geometric topological features refer to the shape characteristics of physical markers, and reflectivity features refer to the lidar reflection intensity characteristics of the surface material of physical markers, used to distinguish physical markers from other environmental objects. Under complex lighting conditions or when physical markers are partially occluded, multi-sensor fusion recognition can utilize the complementary characteristics of different sensors to improve the robustness and accuracy of recognition.

[0028] In an alternative approach, physical marker identification can also employ a purely visual recognition method. The specific implementation is as follows: The robot acquires environmental images containing physical markers using onboard vision sensors, which can be monocular, binocular, or depth cameras. Image recognition algorithms process the acquired environmental images, detecting and identifying physical markers from the images based on their shape, color, reflectivity, or visual coding features, determining the pixel coordinates of each physical marker in the image. The spatial position information of each physical marker is calculated according to the type of vision sensor. For example, when using binocular cameras, the three-dimensional spatial coordinates of the physical markers in the robot's coordinate system are calculated using the parallax information obtained from the left and right cameras and the principle of triangulation. When using a depth camera, the depth value of the corresponding pixel position in the depth image is directly read, and the pixel coordinates are converted into three-dimensional spatial coordinates using camera intrinsic parameters. When using a monocular camera, the distance between the physical marker and the robot is estimated using the prior size information of the physical marker and the ratio between the pixel size and the prior size, thereby obtaining the spatial position information.

[0029] In an alternative approach, physical marker identification can also employ a pure optical ranging sensor method. The specific implementation is as follows: The robot scans the working environment using an onboard optical ranging sensor, which may include a lidar sensor. The optical ranging sensor emits a light beam and receives the reflected signal from the surface of the physical marker. Based on the time difference or phase difference between the beam emission and the received reflected signal, the distance between the optical ranging sensor and the physical marker is calculated. Simultaneously, the optical ranging sensor records the horizontal and vertical scanning angles at the time of beam emission. Combining this with the measured distance value, the spatial position information of the physical marker in the optical ranging sensor's coordinate system is calculated using a polar-to-Cartesian coordinate transformation formula. For example, when the optical ranging sensor is a single-line lidar, the two-dimensional spatial position information of the physical marker is acquired; when the optical ranging sensor is a multi-line lidar, the three-dimensional spatial position information of the physical marker is acquired. By extracting the reflectivity characteristics of the physical marker, it is distinguished from other environmental objects. Point cloud clusters belonging to the physical marker are identified from the scanned point cloud, and the coordinates of their center points are used as the spatial position information of the physical marker.

[0030] The advantages of adopting the above operation are as follows: By controlling the robot to automatically identify physical landmarks and obtain their spatial location information, the robot can directly utilize commonly used physical landmarks on site, avoiding the operational complexity and risk of misoperation caused by manually drawing the boundaries of the work area on the terminal interface, and reducing additional hardware and deployment costs. On the other hand, through multi-sensor fusion recognition using visual sensors and optical ranging sensors, the robustness of physical landmark recognition under complex lighting or partial occlusion conditions is improved, ensuring the accuracy of spatial location information acquisition.

[0031] S2, based on spatial location information, sorts and connects physical markers to obtain the target operation boundary. The specific implementation is as follows: Based on the acquired spatial location information of each physical marker, the spatial distribution geometric relationship between them is analyzed. This spatial distribution geometric relationship refers to the geometric features of the point set calculated based on the spatial location information of each physical marker, including the coordinates of the geometric center of all physical marker points, the polar angle of each physical marker relative to the geometric center, the Euclidean distance between each physical marker, and the minimum convex hull shape of the point set. Based on this spatial distribution geometric relationship, the connection order of each physical marker is determined. Adjacent physical markers are then connected sequentially with line segments to form a closed polygonal boundary, which is the target operation boundary. The target operation boundary defines the area within which the robot is allowed to operate.

[0032] In a preferred embodiment, the physical markers are sorted and connected, specifically by using any one of the following: polar angle sorting strategy, convex hull algorithm, polygon fitting algorithm or shortest closed loop generation algorithm, to sort and connect the physical markers according to spatial location information to obtain the target operation boundary.

[0033] The polar angle sorting strategy is implemented as follows: calculate the geometric center coordinates of all physical markers, take the geometric center as the reference pole, calculate the polar angle of the line connecting each physical marker and the reference pole, arrange the physical markers in order of increasing polar angle, connect adjacent physical markers with line segments in turn, and connect the first and last physical markers to obtain a closed polygon as the target operation boundary.

[0034] The convex hull algorithm is implemented as follows: Calculate the smallest convex polygon containing all physical markers. The vertices of this convex polygon are some of the physical markers. Connect these vertices in a counterclockwise or clockwise order to obtain a convex closed boundary as the target operation boundary.

[0035] The polygon fitting algorithm is implemented as follows: Based on the spatial location information of each physical marker, an approximate polygon is generated as the target operation boundary using a fitting method. This approximate polygon can reflect the overall distribution trend of the physical markers.

[0036] The shortest loop generation algorithm is implemented as follows: Each physical marker is considered a node to be traversed. The shortest closed loop, which passes through all nodes, is found and represents the target operation boundary. The shortest loop generation algorithm can be implemented based on an approximate solution method for the Traveling Salesman Problem (TSP).

[0037] The advantages of employing the above methods are as follows: By automatically sorting and connecting physical markers to generate the target operation boundary, the construction of the operation area boundary is automated, reducing manual setup steps and improving the rapid deployment capability in temporary operation scenarios. Furthermore, by providing multiple sorting and connection algorithms, the method can adapt to different distribution patterns of physical markers, improving its versatility and flexibility.

[0038] After obtaining the target operation boundary, the process also includes: validating the target operation boundary; the validity check includes at least one of the following: determining whether the target operation boundary is closed, determining whether the target operation boundary has self-intersections, determining whether the area enclosed by the target operation boundary is greater than a preset area threshold, and determining whether the distance between adjacent physical markers is within a preset distance range. The specific implementation method is as follows: After generating the target job boundary, the target job boundary is validated for legality.

[0039] The method for determining whether the target operation boundary is closed is as follows: check whether the physical markers at the beginning and end of the target operation boundary are connected, that is, compare whether the coordinates of the first node and the last node are consistent, or whether the deviation between the two is within the preset error range. If they are inconsistent, the target operation boundary is determined to be unclosed.

[0040] The method for determining whether the target operation boundary has self-intersection is as follows: traverse all non-adjacent boundary segments in the target operation boundary, calculate whether there is an intersection point between each pair of boundary segments, and if there is an intersection point, determine that the target operation boundary has self-intersection.

[0041] The method for determining whether the area enclosed by the target operation boundary is greater than the preset area threshold is as follows: Calculate the area of ​​the region enclosed by the target operation boundary using the polygon area formula, and compare the calculated area with the preset area threshold. If the area is less than or equal to the preset area threshold, it is determined that the area enclosed by the target operation boundary does not meet the preset area threshold and cannot meet the space requirements for normal robot operation.

[0042] The method for determining whether the distance between adjacent physical markers is within the preset distance range is as follows: the Euclidean distance between adjacent physical markers is calculated to determine whether the distance between adjacent physical markers is within the preset distance range. If the distance between any adjacent physical markers exceeds the preset distance range, it is determined that the arrangement of physical markers is unreasonable, which may lead to long sides or overly dense sides at the target operation boundary.

[0043] In an alternative approach, legality verification can also be based on the matching relationship between the target operation boundary and the two-dimensional environment map information. The two-dimensional environment map information refers to the environmental contour or grid map constructed in real time by the robot using Simultaneous Localization and Mapping (SLAM) technology. The specific implementation of legality verification based on the matching relationship between the target operation boundary and the two-dimensional environment map information is as follows: The robot acquires a two-dimensional grid map or environmental contour map of the operation environment using SLAM technology. This two-dimensional environment map records the positions of fixed obstacles and walkable areas in the environment. The robot projects the target operation boundary onto the coordinate system of the two-dimensional environment map and selects at least one of the following verification operations: Verify whether the area enclosed by the target operation boundary is entirely within the walkable area. If any part of the target operation boundary overlaps with the positions of fixed obstacles in the two-dimensional environment map, or crosses an obstacle area, the legality verification fails. Verify whether the target operation boundary exceeds the known area of ​​the map. If the target operation boundary exceeds the boundary of the known area of ​​the two-dimensional environment map, the legality verification fails, and the operator is prompted to supplement the map or adjust the positions of physical landmarks. By matching and comparing the target operation boundary with the environmental map constructed by SLAM, the robot can avoid setting the operation area in the location of obstacles or in unmapped areas, thus improving operation safety.

[0044] Once the legality verification is successful, the robot continues to execute subsequent work processes; if the legality verification fails, the robot outputs an alarm message, prompting the operator to adjust the placement or quantity of physical markers.

[0045] The beneficial effects of adopting the above operation are as follows: by performing multiple checks on the closure, self-intersection, area rationality, and physical marker spacing of the target operation boundary, the illegality of the target operation boundary caused by improper placement of physical markers or recognition errors is effectively avoided, thereby improving the safety and reliability of robot operation.

[0046] After obtaining the target work boundary, the process also includes: shifting the target work boundary inwards by a preset safety distance to generate a safe work area. The specific implementation is as follows: After obtaining the target work boundary, to prevent the robot from getting too close to physical landmarks or crossing the target work boundary during operation, the target work boundary is shifted inward by a preset safety distance, generating a reduced safe work area. The inward direction of the target work boundary refers to the direction towards the inside of the polygon enclosed by the target work boundary. The preset safety distance can be set according to the robot's dimensions, motion control accuracy, and the safety requirements of the task.

[0047] In an alternative approach, the safe working area can be generated using different offset distances or dynamic adjustment strategies. For example, the offset distance can be dynamically adjusted based on the robot's current operating speed; the faster the robot's current operating speed, the larger the preset safe distance. The translation can be implemented using an angle bisector offset algorithm: for each vertex of the target working boundary, calculate the direction of the angle bisector between the two sides at that vertex, and move the vertex inwards along the angle bisector by a preset safe distance to obtain a new translated vertex; for each side of the target working boundary, calculate the normal vector inwards along that side, and translate the new side by a preset safe distance to obtain a new translated side; recalculate the intersection points of the new translated sides to obtain the vertex sequence of the safe working area. Through this translation process, the robot is confined to the safe working area during actual operation, maintaining a preset safe distance from physical landmarks.

[0048] The beneficial effect of adopting the above operation is that by shifting the target operation boundary inward to generate a safe operation area, the robot is effectively prevented from colliding with physical markers or accidentally crossing the target operation boundary during operation, thereby improving the safety of the operation process.

[0049] After obtaining the target operation boundary, the process also includes: during the operation, real-time monitoring of the spatial position information of each physical marker, calculating the displacement based on the spatial position information of each physical marker before and after the change; when the displacement exceeds a preset displacement threshold or the number of physical markers changes, repeat step S2 to update the target operation boundary. The specific implementation method is as follows: During the operation, the robot continuously monitors the spatial position information of each physical marker through environmental perception sensors. It acquires the current spatial position information of each physical marker in real time and compares it with previously stored spatial position information to calculate the displacement of each physical marker before and after the change. The displacement refers to the Euclidean distance between the spatial position information of the same physical marker at two different times. It also monitors whether the number of physical markers has changed, i.e., whether the currently detected number of physical markers is consistent with the initial number. When the displacement of any physical marker exceeds a preset displacement threshold, or when the number of physical markers increases or decreases, it is determined that the target operation boundary has been adjusted by on-site personnel. In response to this determination, the robot automatically suspends the current operation, extracts the spatial position information of each physical marker after the change, re-executes step S2, i.e., re-sorts and connects the physical markers according to the changed spatial position information to obtain the updated target operation boundary, and resumes the operation.

[0050] After receiving the updated target work boundary, the robot can re-perform the legality check and generate the safe work area, and resume work after updating the safe work area in real time.

[0051] The beneficial effects of the above operation are: by monitoring the changes in the position and quantity of physical markers in real time, the dynamic reconstruction of the target operation boundary is automatically triggered when changes are detected, enabling the robot to adapt to the actual scenario where physical markers are moved or added or removed during the operation, thereby improving the robustness and on-site adaptability of the method.

[0052] After generating the safe work area, the process also includes a work area data output step. The specific implementation is as follows: The target work boundary or safe work area is output as polygon data and map data for use by the robot's subsequent work path planning and motion control modules. The robot's subsequent work path planning is based on the target work boundary or safe work area to plan the robot's travel path, and the motion control module controls the robot's movement according to the planning results to ensure that the robot operates autonomously within the target work boundary or safe work area.

[0053] The beneficial effect of adopting the above operation is that by outputting the safe working area in the form of standardized data, reliable constraint data is provided for the robot's path planning and motion control, realizing a complete closed loop from the construction of the working boundary to the execution of the operation.

[0054] The beneficial effects of the automatic construction method for work areas based on physical markers provided by this invention are as follows: Without the need for pre-built maps or fixed boundary facilities, the robot can automatically identify the physical markers already placed on site and obtain their spatial location information. Based on the spatial location information, the physical markers are sorted and connected to obtain the target operation boundary. This enables the direct use of commonly used physical markers on site and the automatic construction of operation boundaries, effectively reducing the risk of manual setting and misoperation, lowering additional hardware and deployment costs, and improving the automation level of robot operation area construction and rapid deployment capability in temporary operation scenarios.

[0055] In the above embodiments, although the steps are numbered S1, S2, etc., they are only specific embodiments given by the present invention. Those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, and these situations are also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0056] Furthermore, the acquisition process of the data involved in this application follows the principles of legality, legitimacy, and necessity. Based on obtaining the explicit authorization and consent of the user, only the minimum necessary information required to achieve the purpose is collected, and data security protection obligations are fulfilled in accordance with the law.

[0057] The present invention also provides an automatic construction system for work areas based on physical markers, the specific technical solution of which includes: an identification and positioning module and a sorting and connection module; The identification and positioning module is used to control the robot to identify multiple physical markers located at the boundary of the work area and obtain the spatial position information of each physical marker; the physical markers are used to define the boundary position of the work area. The sorting and connection module is used to sort and connect physical markers based on spatial location information to obtain the target operation boundary.

[0058] It should be noted that the beneficial effects of the automatic work area construction system based on physical markers provided in the above embodiments are the same as those of the automatic work area construction method based on physical markers described above, and will not be repeated here. Furthermore, the system provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to the actual situation to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiments, and will not be repeated here.

[0059] like Figure 2As shown, an embodiment of the present invention provides a computer device 300, which includes a processor 320 coupled to a memory 310. The memory 310 stores at least one computer program 330, which is loaded and executed by the processor 320 to enable the computer device 300 to implement any of the above-described methods. Specifically: The computer device 300 can vary considerably due to differences in configuration or performance. It may include one or more processors 320 (Central Processing Units, CPUs) and one or more memories 310. The one or more memories 310 store at least one computer program 330, which is loaded and executed by the one or more processors 320 to enable the computer device 300 to implement the method for automatically constructing a work area based on physical markers provided in the above embodiments. Of course, the computer device 300 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The computer device 300 may also include other components for implementing device functions, which will not be elaborated upon here.

[0060] An embodiment of the present invention provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to enable a computer to implement any of the above-described methods.

[0061] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0062] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the above-described methods for automatically constructing work areas based on physical markers.

[0063] It should be noted that the terms "first," "second," etc., used in the specification of this application are used to distinguish similar objects and do not imply a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown in the figures or description.

[0064] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0065] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0066] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for automatically constructing work areas based on physical markers, characterized in that, include: S1, control the robot to identify multiple physical markers located at the boundary of the work area and obtain the spatial position information of each physical marker; The physical markers are used to define the boundary positions of the area to be worked on; S2, based on the spatial location information, sort and connect the physical markers to obtain the target operation boundary.

2. The method for automatically constructing a work area based on physical markers according to claim 1, characterized in that, The identification of multiple physical markers located at the boundary of the work area includes: The robot uses its environmental perception sensors to perform multi-sensor fusion recognition of the physical markers. The environmental perception sensors include a visual sensor and an optical ranging sensor.

3. The method for automatically constructing a work area based on physical markers according to claim 1, characterized in that, The sorting and linking of the physical markers specifically includes: By employing any one of the polar angle sorting strategy, convex hull algorithm, polygon fitting algorithm, or shortest closed loop generation algorithm, the physical markers are sorted and connected according to the spatial location information to obtain the target operation boundary.

4. The method for automatically constructing a work area based on physical markers according to claim 1, characterized in that, After obtaining the target job boundary, the method further includes: performing a legality check on the target job boundary; The legality verification includes at least one of the following: determining whether the target operation boundary is closed, determining whether the target operation boundary has self-intersection, determining whether the area enclosed by the target operation boundary is greater than a preset area threshold, and determining whether the distance between adjacent physical markers is within a preset distance range.

5. The method for automatically constructing a work area based on physical markers according to claim 1, characterized in that, After obtaining the target operation boundary, the process also includes: The target work boundary is shifted inward by a preset safety distance to generate a safe work area.

6. The method for automatically constructing a work area based on physical markers according to claim 1, characterized in that, After obtaining the target operation boundary, the process also includes: During the operation, the spatial position information of each physical marker is monitored in real time, and the displacement is calculated based on the spatial position information of each physical marker before and after the change. When the displacement exceeds a preset displacement threshold or the number of physical markers changes, repeat step S2 to update the target work boundary.

7. An automated work area construction system based on physical markers, characterized in that, include: Identification and positioning module and sorting and connection module; The identification and positioning module is used to control the robot to identify multiple physical markers located at the boundary of the work area and obtain the spatial position information of each physical marker; the physical markers are used to define the boundary position of the work area. The sorting and connection module is used to sort and connect the physical markers according to the spatial location information to obtain the target operation boundary.

8. The automatic construction system for work areas based on physical markers according to claim 7, characterized in that, The identification of multiple physical markers located at the boundary of the work area includes: The robot uses its environmental perception sensors to perform multi-sensor fusion recognition of the physical markers. The environmental perception sensors include a visual sensor and an optical ranging sensor.

9. A computer device, characterized in that, The computer device includes a processor coupled to a memory storing at least one computer program, which is loaded and executed by the processor to enable the computer device to implement a method for automatically constructing a work area based on physical markers as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer program, which is loaded and executed by a processor to enable the computer to implement a method for automatically constructing a work area based on physical markers as described in any one of claims 1 to 6.

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