Intelligent system, control method for autonomous mobile device, and storage medium

Abstract

An intelligent system, a control method for an autonomous mobile device (10), and a storage medium. The intelligent system comprises: a base station (20), which is provided with a concave arc-shaped structure (22) for accommodating an autonomous mobile device (10), and the autonomous mobile device (10), wherein two ends of the concave arc-shaped structure (22) are respectively connected to two end faces (24a, 24b), and normal directions of the two end faces (24a, 24b) are consistent with the orientation of the base station; and the autonomous mobile device (10) is used for obtaining point cloud data from a lidar, recognizing, from the point cloud data, a first group of laser points, a second group of laser points and a third group of laser points, which respectively represent the two end faces (24a, 24b) and the concave arc-shaped structure (22), determining the directions of the end faces according to a first straight line and / or a second straight line, determining the position of the circle center (C) of the concave arc-shaped structure (22) according to the third group of laser points, and determining the pose of the base station according to the position of the circle center (C) of the concave arc-shaped structure (22) and the normal directions of the end faces. Thus, the autonomous mobile device (10) can determine the pose of the base station (20) at a lower cost and with a lower computing power requirement, so as to drive into the base station (20).

Description

Intelligent system, control method of autonomous mobile device and storage medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on June 27, 2023, with application number 202310770121.3 and application name “Intelligent system, control method and storage medium for autonomous mobile device”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present disclosure relates to the field of smart home technology, and in particular to an intelligent system, a control method for an autonomous mobile device, and a storage medium. Background Art

[0003] With the continuous development of autonomous mobile device technology, intelligent systems with various uses have emerged. Intelligent systems include autonomous mobile devices and matching base stations. Autonomous mobile devices can move on the work surface of a work area to complete specific tasks (such as cleaning, item delivery, and patrolling). To do this, the autonomous mobile device needs to obtain a map of the work area and determine the position of the autonomous mobile device itself. Common methods for creating maps and determining position include simultaneous localization and mapping (SLAM) technology.

[0004] In laser SLAM technology, a mechanical laser radar (hereinafter referred to as a 360-degree laser radar) installed on an autonomous mobile device with 360-degree rotational scanning is often used to detect object information in the working area to achieve positioning, mapping, and determine its own posture. Specifically, when the 360-degree laser radar rotates around an axis of rotation perpendicular to the ground, it scans the surrounding area on a horizontal plane and receives reflected laser light reflected by objects in the working area (hereinafter referred to as environmental objects). This allows it to detect multiple laser points representing environmental objects at corresponding angles and distances in the working area and form a "point cloud." The laser radar continuously rotates 360 degrees at a certain frequency, and each rotation produces a series of laser points reflected by surrounding environmental objects. All of these laser points collectively represent the outline of the corresponding environmental object in the working area facing the laser radar, which is called point cloud data. SLAM can be implemented based on point cloud data using specific algorithms (such as cartographer, karto, or gmapping).

[0005] The base station of the intelligent system provides auxiliary functions for autonomous mobile devices, such as charging, docking, and even cleaning. For example, after completing a cleaning task or when the battery level is low, the autonomous mobile device needs to return to the base station for charging. Autonomous mobile devices also typically dock at the base station when not performing tasks, waiting for the next task. Typically, autonomous mobile devices need to accurately and autonomously navigate to a specific location within the base station. For example, if charging is required, the autonomous mobile device must precisely align its charging contacts with the charging contacts on the base station upon entering the base station for charging.

[0006] Therefore, in order for an autonomous mobile device to accurately and autonomously drive to such a specific location in the base station, the autonomous mobile device needs to locate such a specific location in the base station (i.e., determine the posture of the base station, including the position and orientation of the base station). Some existing technologies provide a method of determining the posture of the base station by sending a guidance signal outward from the base station and receiving the guidance signal by a receiver on the autonomous mobile device; some existing technologies use an image sensor (such as a camera) to capture specific image features attached or set at a specific location on the base station to determine the posture of the base station. However, these solutions require additional hardware equipment, thereby increasing costs. On the other hand, these solutions require processing additional signals, which increases the computational workload of the processor.

[0007] Summary of the Invention

[0008] The purpose of the present disclosure is to overcome or at least alleviate the deficiencies of the above-mentioned prior art and to provide an intelligent system, a control method for an autonomous mobile device, and a computer-readable storage medium.

[0009] In a first aspect of the present disclosure, an intelligent system is provided, comprising: a base station having an inwardly concave arc structure for accommodating an autonomous mobile device, and two end faces at both ends of the inwardly concave arc structure and connected to the two ends of the inwardly concave arc structure, wherein the normal direction of the two end faces is consistent with the orientation of the base station; and the autonomous mobile device comprising: a motion component configured to move the autonomous mobile device on a working surface in a working area; a laser radar configured to emit laser light to the surroundings of the autonomous mobile device within a predetermined angle range, and receive reflected laser light of the laser light to obtain point cloud data, wherein the laser light forms a laser surface on a plane parallel to the working surface; a memory storing instructions; and a processor configured to call the instructions to perform the following steps: obtaining the point cloud data from the laser radar; identifying a first group of laser points, a second group of laser points, and a plurality of laser points from the point cloud data; and a third group of laser points, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; if a first condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end faces, wherein the first condition includes: the first group of laser points can be fitted as a first straight line in the laser surface, the second group of laser points can be fitted as a second straight line in the laser surface, and the first straight line and the second straight line have the same normal direction; the direction of the end face is determined according to the first straight line and / or the second straight line, and the position of the center of the concave arc structure is determined according to the third group of laser points; and the posture of the base station is determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

[0010] In a second aspect of the present disclosure, an intelligent system is provided, comprising: a base station having an inwardly concave arc structure for accommodating an autonomous mobile device, and two end faces at both ends of the inwardly concave arc structure and connected to the two ends of the inwardly concave arc structure, wherein the normal direction of the two end faces is consistent with the orientation of the base station; and the autonomous mobile device comprising: a motion component configured to move the autonomous mobile device on a working surface in a working area; a laser radar configured to emit laser light to the surroundings of the autonomous mobile device within a predetermined angle range and receive reflected laser light of the laser light to obtain point cloud data, wherein the laser light forms a laser surface on a plane parallel to the working surface, a memory storing instructions; and a processor configured to call the instructions to perform the following steps: obtaining the point cloud data from the laser radar; identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group The laser point and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; if the second condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a part of each of the two end faces, wherein the second condition includes: the third group of laser points can be fitted as an arc within the laser surface, and the arc can match the shape of the projection of the concave arc structure on the laser surface; if the first group of laser points can be fitted as a first straight line within the laser surface or the second group of laser points can be fitted as a second straight line within the laser surface, the direction of the end face is determined according to the first straight line or the second straight line, and the position of the center of the concave arc structure is determined according to the third group of laser points; and the posture of the base station is determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

[0011] In a third aspect of the present disclosure, an intelligent system is provided, comprising: a base station having a concave arc-shaped structure for accommodating an autonomous mobile device; and the autonomous mobile device comprising: a motion component configured to move the autonomous mobile device on a working surface in a working area; a laser radar configured to emit laser light to the surroundings of the autonomous mobile device within a predetermined angle range and receive reflected light of the laser light to obtain point cloud data, wherein the laser light forms a laser surface on a plane parallel to the working surface; a memory storing instructions; and a processor configured to call the instructions to perform the following steps: obtaining the point cloud data from the laser radar; and determining the position of the center of the concave arc-shaped structure based on the point cloud data.

[0012] In a fourth aspect of the present disclosure, a control method for an autonomous mobile device is provided, the autonomous mobile device being an autonomous mobile device in the intelligent system according to the first aspect above, the control method comprising: obtaining the point cloud data from the laser radar; identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; if a first condition is satisfied, determining that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end faces, wherein the first condition includes: the first group of laser points can be fitted as a first straight line within the laser surface, the second group of laser points can be fitted as a second straight line within the laser surface, and the first straight line and the second straight line have the same normal direction; determining the direction of the end face based on the first straight line and / or the second straight line, and determining the position of the center of the concave arc structure based on the third group of laser points; and determining the position of the base station based on the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

[0013] In a fifth aspect of the present disclosure, a control method for an autonomous mobile device is provided, wherein the autonomous mobile device is an autonomous mobile device in the intelligent system according to the second aspect above, and the control method comprises: obtaining the point cloud data from the laser radar; identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; if a second condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end faces, wherein the second condition includes: the third group of laser points can be fitted into an arc within the laser surface, and the arc can match the shape of the projection of the concave arc structure on the laser surface; if the first group of laser points can be fitted into a first straight line within the laser surface or the second group of laser points can be fitted into a second straight line within the laser surface, then determining the direction of the end face according to the first straight line or the second straight line, and determining the position of the center of the concave arc structure according to the third group of laser points; and determining the posture of the base station according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

[0014] In the sixth aspect of the present disclosure, a control method for an autonomous mobile device is provided, wherein the autonomous mobile device is an autonomous mobile device in the intelligent system according to the third aspect above, and the control method includes: obtaining the point cloud data from the laser radar; and determining the position of the center of the concave arc structure based on the point cloud data.

[0015] In a seventh aspect of the present disclosure, a computer-readable storage medium is provided, which stores a computer program including instructions, which implement the above-mentioned control method when executed by a processor of an autonomous mobile device.

[0016] According to the technical solution disclosed herein, the autonomous mobile device determines the center of the base station's concave arc structure based on point cloud data obtained from a laser radar. This allows the device to determine the base station's approximate location, enabling the autonomous mobile device to quickly approach the base station. Because the base station's approximate location can be determined without adding additional components, circuits, or algorithms to the base station, the increased cost associated with determining the base station's location is avoided. Furthermore, the autonomous mobile device processes the point cloud data obtained from the laser radar during normal operation during the base station search process, eliminating the need to process additional signals specifically for base station search, thereby conserving processor computing power.

[0017] According to the technical solution disclosed in the present invention, in addition to determining the position of the center of the concave arc structure of the base station based on the point cloud data obtained from the laser radar, the autonomous mobile device also determines the normal direction of at least one of the two end faces of the concave arc structure of the base station based on the point cloud data, thereby determining the orientation of the base station, and thus determining the posture of the base station. The autonomous mobile device determines the exact position of the base station based on the posture of the base station, so that the autonomous mobile device can efficiently and accurately enter the base station, thereby performing corresponding charging and / or cleaning tasks such as dust removal.

[0018] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0020] FIG. 1 shows a schematic diagram of an intelligent system according to an exemplary embodiment.

[0021] FIG. 2 shows a schematic diagram of point cloud data according to an exemplary embodiment.

[0022] FIG3 illustrates a flowchart of a control method of an autonomous mobile device according to an exemplary embodiment.

[0023] FIG. 4 is a schematic diagram illustrating positioning the center of a concave arc-shaped structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0024] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0025] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0026] In addition, numerous specific details are provided in the following detailed description to better illustrate the present disclosure. Those skilled in the art will appreciate that the present disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main points of the present disclosure.

[0027] FIG1 illustrates a schematic diagram of an intelligent system according to an exemplary embodiment. Referring to FIG1 , the intelligent system may include an autonomous mobile device 10 and a base station 20, wherein the autonomous mobile device 10 is traveling back to the base station 20. It should be understood that if the autonomous mobile device 10 needs to return to the base station 20, for example, to charge and / or clean the autonomous mobile device 10, the autonomous mobile device 10 may return to the base station 20. Similarly, if the autonomous mobile device 10 needs to leave the base station 20, for example, to perform a task on a work surface in a work area, the autonomous mobile device 10 may travel away from the base station 20.

[0028] The base station 20 has a concave arc-shaped structure 22, which is used to accommodate the autonomous mobile device 10 that is driven back to the base station 20. The concave arc-shaped structure 22 has a defined and known radius and center (referred to as the center of the concave arc structure in this disclosure). Referring to FIG. 1 , in this embodiment, the concave arc-shaped structure 22 is a symmetrical structure having an axis of symmetry (i.e., the dashed line in FIG. 1 ). In this disclosure, the orientation of the base station 20 refers to the direction along the axis of symmetry of the concave arc structure 22, pointing from the concave arc structure 22 to the center of the concave arc structure 22.

[0029] In some embodiments, referring to FIG. 1 , the base station 20 has two end surfaces 24a and 24b at opposite ends of the inwardly concave arc-shaped structure 22, respectively connected to the opposite ends of the inwardly concave arc-shaped structure 22. The end surfaces 24a and 24b are substantially parallel or coplanar. In an exemplary embodiment, both end surfaces 24a and 24b are perpendicular to the ground, and the normal directions of the two end surfaces 24a and 24b (i.e., the directions perpendicular to the end surfaces) are substantially aligned with the orientation of the base station 20. In practice, the normal directions of the two end surfaces 24a and 24b may have a certain tolerance (e.g., ±5°) to each other, which also means that the end surfaces 24a and 24b are substantially parallel or coplanar. The normal directions of each end surface 24a and 24b may also have a certain tolerance (e.g., ±5°) to the orientation of the base station 20, which also means that the normal directions of each end surface 24a and 24b are substantially aligned with the orientation of the base station 20.

[0030] Because the location where the front or rear profile of the autonomous mobile device 10 meets the concave curved structure 22 at the front end of the base station 20 typically has a curved outer profile, when the autonomous mobile device 10 is properly parked at the base station 20, the curved outer profile of the autonomous mobile device 10 can enter and mate with the concave curved structure of the base station 20. Therefore, once the autonomous mobile device 10 determines the position and orientation of the base station 20 (collectively referred to as its posture), it can move toward the base station 20 and ultimately accurately dock at a specific location within the base station 20. For example, as shown in Figure 1, two charging contacts are typically positioned symmetrically at the front end of the base station 20, with the connection direction of these two charging contacts typically perpendicular to the orientation of the base station 20. When the autonomous mobile device 10 is docked at the base station 20, the charging contacts of the autonomous mobile device 10 mate with the charging contacts of the base station 20, allowing the base station 20 to charge the autonomous mobile device 10.

[0031] The autonomous mobile device 10 may include a motion assembly 12 for enabling the autonomous mobile device 10 to move across a work surface within a work area. The autonomous mobile device 10 may also include a memory 16 storing instructions. The autonomous mobile device 10 may also include a processor 18 for invoking the instructions in the memory 16 to execute the steps described below, thereby controlling the various components of the autonomous mobile device 10 to perform corresponding operations.

[0032] The autonomous mobile device 10 may also include a laser radar 14. The laser radar 14 emits laser light (e.g., a point laser beam) into the surrounding environment. The laser beam emitted by the laser radar 14 reflects light from objects in the environment and can be received by the laser radar 14. Based on the emitted laser light and the received reflected laser light, the distance data between the autonomous mobile device 10 and the objects in the environment can be calculated. The "point" formed by the emitted laser beam irradiating the objects in the environment and received by the laser radar is referred to as a laser point in this disclosure.

[0033] In an exemplary embodiment, the time of flight (TOF) method is used to calculate the distance data between the autonomous mobile device 10 and the environmental objects. The laser radar 14 records the emission time of the laser and the reception time of the reflected light, and calculates the time difference Δt from the emission time to the reception time of the same laser beam, that is, the flight time of the laser; since the speed of light c is known, the distance l between the autonomous mobile device 10 and the environmental objects can be calculated by 2×l=c·Δt. In some embodiments, the laser radar 14 is communicatively connected to the processor 18, and the recording of the emission time and the reception time of the laser beam and the related calculations are completed by the processor 18 by calling the instructions in the memory 16. Of course, other methods in the prior art, such as triangulation, can also be used to calculate the distance, and the functions of detection, data processing and calculation can also be completed by other components of the circuit on the laser radar 14. The present disclosure does not impose specific restrictions on this.

[0034] The laser radar 14 can be a mechanical laser radar capable of 360-degree rotational scanning, but it can also be a laser radar that rotates and scans within a non-circular angle range (such as rotational scanning within an angle range of 210 degrees), or a non-rotating laser radar such as a pure solid-state laser radar (such as an OPA optical phased array radar or a flash laser radar, etc.), and the present disclosure does not impose any restrictions on this. Common laser radars, except for point laser sources, need to emit fan-shaped or circular lasers within a certain angle range around them. The emitted laser mentioned here includes the laser emitted after passing through a rotating mirror. For the convenience of subsequent description, in the present disclosure, the surface formed by the laser emitted by the laser radar within a predetermined angle range around it on a plane parallel to the working surface (such as the ground) of the autonomous mobile device 10 is called a laser surface. For example, for a 360-degree rotating mechanical laser radar, the laser is emitted in a direction perpendicular to the laser radar's rotation axis, and the surface swept by the laser after 360-degree rotation is the laser surface; for a laser radar that refracts the laser after being emitted by a rotating mirror, the surface perpendicular to the rotating mirror's rotation axis is the laser surface; and for a non-rotating pure solid-state laser radar, the surface perpendicular to the solid-state laser radar's transmitting or receiving array (surface array) and parallel to the working surface is the laser surface. In an exemplary embodiment, on the laser surface, the laser points formed after the laser emitted by the laser radar 14 hits the environmental objects are received by the laser radar, thereby obtaining 2D (two-dimensional) point cloud data within the laser surface. When the rear of the base station 20 as shown in Figure 1 is placed against the wall, the laser radar 14 can obtain the 2D point cloud data shown in Figure 2, which includes laser points representing the concave arc structure 22 (such as the dotted area A in Figure 2) and laser points on the walls on both sides (such as areas B1 and B2 in Figure 2). In this disclosure, for the convenience of description, even if a 3D (three-dimensional) laser radar is used, such as a hybrid solid-state laser radar using a two-dimensional rotating mirror or a MEMS micro-vibration mirror, or a non-rotating pure solid-state laser radar, according to the laser surface defined above, the obtained 3D point cloud data will be converted into 2D point cloud data within the laser surface during the description process.

[0035] It should be understood that for simplicity, Figure 1 only illustrates some components of the autonomous mobile device 10 and base station 20 of the intelligent system. However, other components may be included within the autonomous mobile device 10 and base station 20 depending on design and / or application requirements. In other words, the autonomous mobile device 10 and base station 20 may also include other components to implement their functions. In an exemplary embodiment, the autonomous mobile device 10 is a cleaning robot, which includes a brush head or mop tray for cleaning and a dust box for storing waste. The autonomous mobile device 10 may also include charging contacts for charging; some models of autonomous mobile devices 10 may also include a removable dust box cover for communicating with the interior of the dust box. The base station 20 may also include a dust box interface that corresponds to the removable dust box cover on the autonomous mobile device 10. When the autonomous mobile device 10 enters the base station 20 and its curved outer contour aligns with the inwardly concave curved structure 22 of the base station 20, the charging contacts and removable dust box cover on the autonomous mobile device 10 mate with the charging contacts and dust box interface on the base station 20, respectively, thereby enabling the charging and emptying of the dust box.

[0036] In order for the autonomous mobile device 10 to enter the base station 20 and be accommodated by the concave arc-shaped structure 22 to perform corresponding charging and / or cleaning tasks, such as emptying the dust box, the autonomous mobile device 10 needs to determine the position and orientation of the base station 20. For convenience, in some embodiments, the position of the base station 20 can be roughly represented by the position of the center of the concave arc-shaped structure 22, and the orientation of the base station 20 can be represented by the direction of the concave arc-shaped structure 22. To this end, the processor 18 of the autonomous mobile device 10 can execute the method shown in Figure 3.

[0037] FIG3 illustrates a flow chart of a control method for an autonomous mobile device according to an exemplary embodiment. The control method 300, executed by the processor 18 by invoking instructions stored in the memory 16, includes: step 310, in which the processor 18 obtains point cloud data from the lidar 14; and step 320, in which the processor 18 determines the center of the concave arc structure 22 based on the point cloud data. Because the center of the concave arc structure 22 is very close to the actual location of the base station 20 (only a distance equal to the radius of the concave arc structure 22), the location of the base station 20 can be roughly determined based on the center. In some exemplary embodiments, the autonomous mobile device 10 can move based on the center of the concave arc structure 22 (i.e., the approximate location of the base station 20). After approaching the approximate location of the base station 20, the autonomous mobile device 10 can then fine-align with the base station 20 by, for example, receiving guidance signals from the base station 20, thereby enabling the autonomous mobile device 10 to enter and accurately dock at the base station 20.

[0038] In some embodiments of the present disclosure, the control method 300 executed by the processor 18 by calling instructions in the memory 16 may also include the following steps: step 330, determining the orientation of the base station 20 based on the point cloud data; and step 340, determining the posture of the base station 20 based on the position of the center of the concave arc structure 22 and the orientation of the base station 20, so that the base station 20 can be accurately positioned to facilitate the autonomous mobile device 10 to accurately and efficiently enter the base station 20.

[0039] In step 310, as described above, the laser radar 14 can obtain 2D point cloud data in the laser plane parallel to the working surface of the autonomous mobile device 10, such as 2D point cloud data in the horizontal plane, which can macroscopically show the outline of objects in the working area within the laser plane scanned by the laser radar 14.

[0040] In an exemplary embodiment, the laser radar 14 has a predetermined detection distance range, that is, only laser light reflected by objects within the detection distance range in the working area will be used by the laser radar 14 to form point cloud data, while laser light reflected by objects outside the detection distance range will not be received by the laser radar 14, or will be discarded by the laser radar 14 and not used as laser points in forming point cloud data, or will not be processed accordingly by the processor 18. For example, the detection distance range can be set to 3 meters, and laser light reflected by objects more than 3 meters around the autonomous mobile device 10 may not be received by the laser radar 14, or may be discarded by the laser radar 14, or may not be processed by the processor 18, to ensure the accuracy of the calculated distance and angle information of the environmental objects. Other detection distance range values ​​can also be set according to specific practices, and this disclosure does not limit this.

[0041] When the autonomous mobile device 10 is within the predetermined detection range of the base station 20, the laser light emitted by the laser radar 14 will illuminate the concave curved structure 22, end surfaces 24a, 24b of the base station 20, and other environmental objects such as surrounding walls or furniture, thereby obtaining a portion of point cloud data as shown in FIG2 . It can be seen that such point cloud data includes laser points representing the concave curved structure 22, end surfaces 24a, 24b, and surrounding walls or furniture. In other words, the laser points reflected by the concave curved structure 22, end surfaces 24a, 24b, and surrounding walls or furniture constitute a portion of the point cloud data.

[0042] Whether in an absolute coordinate system or a relative coordinate system, the position of each laser point in the point cloud data has corresponding coordinates, that is, the coordinates of the environmental objects illuminated by the laser point. In an exemplary embodiment, the processor 18 can use the SLAM algorithm to obtain the coordinates of the surrounding environmental objects based on the point cloud data obtained from the lidar 14, and then obtain a map of the working area. In the map, each laser point in the point cloud data has an absolute coordinate (with a certain point in the environment as a reference point, such as the position of the base station 20 as the origin of the absolute coordinate system). In another embodiment, each laser point in the point cloud data can have relative coordinates relative to the autonomous mobile device 10 (for example, with the position of the autonomous mobile device 10 itself as the origin of the relative coordinate system).

[0043] In step 320, the center position of the concave arc-shaped structure 22 can be determined based on the point cloud data. Specifically, in an exemplary embodiment, step 320 includes sub-steps 322-326. In sub-step 322, multiple construction circles are constructed using the positions of the laser points in the point cloud data as the centers of the construction circles and the radius of the concave arc-shaped structure 22 as the radius of the construction circles. Each construction circle includes at least a portion of an arc. As mentioned above, the radius of the concave arc-shaped structure 22 is known.

[0044] FIG4 illustrates a schematic diagram of determining the center position of a concave arc structure according to an exemplary embodiment, showing multiple examples of constructed circles obtained after executing sub-step 322 based on the laser points in the point cloud data of FIG2 . FIG4 illustratively illustrates only constructed circles obtained based on a portion of the laser points in the point cloud data. For example, to reduce computational overhead, constructed circles may be formed using only laser points within the detection range of the lidar. However, it is understood that other criteria may be used to select a portion of the laser points in the point cloud data to form constructed circles, or all laser points in the point cloud data may be used to form all constructed circles.

[0045] In sub-step 324, for each pair of intersecting constructed circles among the obtained constructed circles, the location of their intersection is obtained. Whether two constructed circles intersect, and if so, their intersection point, can be calculated by combining equations for multiple constructed circles in a coordinate system. Intersection points can also be obtained through image processing methods such as contour extraction (for example, by extracting contours from an image containing multiple constructed circles, the pixels belonging to each pair of intersecting contours are considered intersection points). As shown in FIG4 , each pair of intersecting constructed circles has one or two intersection points.

[0046] In sub-step 326 , the position of the center C of the concave arc-shaped structure 22 is determined based on the intersection point obtained in the above steps.

[0047] Because the laser points on the concave arc-shaped structure 22 are located on the same circle, namely, the circumference of the circle on which the concave arc-shaped structure 22 is located, the constructed circles obtained with the laser points on the concave arc-shaped structure 22 as the center intersect at least at the center C of the concave arc-shaped structure 22. In other words, if the two constructed circles obtained based on the two laser points on the concave arc-shaped structure 22 have only one intersection point, then this intersection point is the center C of the concave arc-shaped structure 22; if they have two intersection points, one of them is the center C of the concave arc-shaped structure 22, and the other intersection point is on the other side of the concave arc-shaped structure 22 (equivalent to the space behind the base station), which is not the location that the autonomous mobile device 10 is expected to reach. In some embodiments, certain constraints are applied when creating the constructed circles, so that the center C representing the concave arc structure can be easily and accurately found through the intersection points of the constructed circles. For example, the base station 20 can be set on the boundary of the working area; then, on the map corresponding to the working area, the coordinates of the center of the concave arc structure 22 on the base station 20 should be within the map of the working area, while the space behind the base station 20 is outside the map. Therefore, the center C of the concave arc structure 22 can be directly determined by limiting the intersection of the constructed circle to within the map.

[0048] In some embodiments, as shown in FIG4 , multiple intersecting construction circles can be obtained based on the laser points in the point cloud data. Each construction circle intersects with at least one other construction circle and generates at least one intersection point, thereby obtaining a plurality of intersection points. However, these laser points used to create the construction circles may be located on the concave arc-shaped structure 22 or may correspond to other objects, such as the aforementioned contacts and interfaces, surrounding walls, and end surfaces 24 a and 24 b. Therefore, the intersection point of any two intersecting construction circles may or may not be the center point C of the concave arc-shaped structure 22. To locate the center point C of the concave arc-shaped structure 22 based on these multiple intersection points, in some embodiments, sub-step 326 further includes detailed steps 3261 to 3263. In step 3261, the set of multiple intersection points is processed as an intersection point set, and in steps 3262 and 3263, the position of the center point C of the concave arc-shaped structure 22 is determined based on the intersection point set.

[0049] In detailed step 3261, the coordinates of each intersection point in the intersection point set can be recorded in an absolute coordinate system or a relative coordinate system. As shown in FIG4 , if the construction circles generated by the laser points on the indented arc-shaped structure 22 intersect, according to geometric knowledge, they should at least have an intersection point at the center C of the indented arc-shaped structure 22. Therefore, many intersection points in the intersection point set will be located at the center C of the indented arc-shaped structure 22, while intersection points not near the center C of the indented arc-shaped structure 22 will not be as concentrated. In an exemplary embodiment, the location of the center C of the indented arc-shaped structure 22 can be determined by finding the location or region with the highest concentration of intersection points between the construction circles.

[0050] Specifically, in detailed step 3262, the number of intersections at the positions of each intersection in the intersection set that falls within the working area is calculated, and then the position of the intersection with the largest number of intersections is determined as the position of the center of the concave arc structure 22. For example, in some embodiments, the processor 18 of the autonomous mobile device 10 has established / stored a grid map of the working area, wherein each position in the working area can be mapped to a corresponding grid on the map and represented by the position of the grid. Therefore, the position of the intersection can be represented by the position of the grid where the intersection lies. If multiple intersections fall within the same grid (i.e., the positions of multiple intersections are all within the area covered by this grid), the grid position can be used to represent the common intersection position of these intersections (i.e., the position of the intersection is represented by the area covered by the grid to increase the count of intersections in similar areas). The number of grids and the size of the grids (i.e., the size of the area covered by each grid) can be determined based on the image resolution. The number of grids and the size of the grids can be determined by those skilled in the art based on actual needs, and this disclosure does not limit this.

[0051] In other embodiments, the absolute or relative coordinates of the intersections may be calculated, and multiple intersections whose coordinate differences (e.g., Euclidean distances) are within a predetermined distance threshold may be identified as having the same intersection position. The predetermined distance threshold may be determined by a person skilled in the art based on actual needs, and the present disclosure does not impose any restrictions thereon. Thus, based on the intersection set, multiple intersection positions may be obtained, the number of intersections falling at each intersection position may be calculated, and the position with the largest number of intersections falling at the intersection position (i.e., the intersection position within a common or similar region of these intersections) may be used as the position of the center C of the concave arc-shaped structure 22.

[0052] Alternatively, in detailed step 3263, a clustering algorithm can be used to cluster the intersection set into several subsets, and the centroid position of each subset can be calculated as the position of the center C of the inward-concave arc structure 22, and the correct position of the center C of the inward-concave arc structure 22 can be identified from the subsets. For example, the intersection set can be clustered using a K-means algorithm, or other algorithms can be used to cluster the intersection set, and this disclosure does not limit this.

[0053] In the implementation using the K-means algorithm, it is expected that (i) the intersection set is clustered into n subsets. It can be understood that, among the n subsets obtained by clustering, one subset includes the intersections concentrated near the center C of the concave arc structure 22, which is the true center position that needs to be identified; and the intersections in the other subsets all need to be excluded. In order to improve efficiency, n-1=1 can be made, that is, all intersections that are not concentrated near the center C are clustered into one subset and excluded. The following description takes n=2 as an example. It is also possible to choose to cluster the intersection set into other numbers of n subsets, and the present disclosure does not limit this.

[0054] In the implementation using the K-means algorithm, then (ii) two points are randomly selected from the intersection set as the centroids; (iii) for each intersection point in the intersection set, the distance between it and each centroid in the two centroids is calculated, and the intersection point is assigned to the subset corresponding to the centroid with the closer distance; (iv) after all the intersection points in the intersection set are assigned to the corresponding subsets, the centroids of the two subsets are recalculated; and (v) for each subset in the two subsets, the distance between the new centroid and the previously randomly selected centroid is calculated. If the distance between the new centroid and the previously randomly selected centroid is greater than a preset threshold, it is indicated that the previously randomly selected centroid is not accurate enough, and the new centroid needs to be used as the centroid and the above steps (iii) to (v) need to be iterated; if the distance between the new centroid and the previously randomly selected centroid is less than or equal to the preset threshold, the clustering result is considered accurate, thereby ending the clustering operation and using the two centroid positions (C and D in FIG4 ) as candidate positions for the center of the concave arc structure 22. Those skilled in the art may also use other algorithms to cluster the intersection set to obtain two or more candidate positions, and the present disclosure does not limit this.

[0055] Next, the true center C of the concave arc structure 22 needs to be identified from the two candidate locations C and D for the center of the concave arc structure 22. It can be seen that, at least for each laser point on the concave arc structure 22 in the point cloud data, the distance between it and the candidate location C is substantially equal to the known radius of the concave arc structure 22. For the other candidate location D, however, only a few laser points in the point cloud data may coincidentally have a distance from the candidate location D equal to the radius of the concave arc structure 22. Therefore, the true center C of the concave arc structure 22 can be identified from the candidate locations C and D by calculating the distances between each laser point in the point cloud data and the candidate location C.

[0056] For example, for each of the two candidate positions C and D of the center of the concave arc structure 22, the distance between the candidate position and each laser point in the point cloud data can be calculated, which is called the "candidate distance". The average value of the candidate distance is calculated based on multiple candidate distances, which is called the "average candidate distance". The standard deviation of the candidate distance is calculated based on the average candidate distance. Preferably, in order to reduce the computational burden and improve accuracy, only the point cloud data within the detection distance range can be used for the calculation. The average candidate distance of the laser point refers to the candidate distance l from the n laser points counted to the candidate position. iThe sum is divided by n. For example, the alternative distance from the first laser point to the candidate position is l1, the alternative distance from the second laser point to the candidate position is l2, ..., the alternative distance from the nth laser point to the candidate position is ln, then the average alternative distance from these n laser points to the candidate position is For each candidate position, the average candidate distance l of the candidate position is obtained. c Afterwards, the candidate distance of each laser point and the average candidate distance l of the candidate position can be calculated c The difference between them, for example, the alternative distance from the i-th laser point to the alternative position is l i , then the alternative distance l from the i-th laser point to the alternative position i Distance to average candidate l c The difference is Δi=l i -l c ; Then consider the n laser points to be counted, for example, The standard deviation of the alternative distance for the alternative position is obtained, which represents the degree of discreteness of the alternative distances of the n laser points from the alternative position. According to geometry, the alternative distances from each laser point on the concave arc structure 22 to the actual alternative position should be relatively close, and should be basically equal to the radius of the concave arc structure (the "basically equal" here takes into account the actual ranging error), that is, the standard deviation of the alternative distance should be small, so the actual alternative position can be determined based on this. For example, for the actual alternative position C, since the alternative distances between the laser point on the concave arc structure 22 in the point cloud data and the actual alternative position C are relatively close and basically equal to the radius of the concave arc structure 22, the standard deviation of the alternative distance of the actual alternative position C is relatively small. Therefore, it can be determined that the alternative position C is the true center of the concave arc structure 22. As for another false alternative position D (this alternative position D is only a mathematical solution, but it is impossible in the actual working area and should be eliminated), the alternative distances between the multiple laser points in the point cloud data and it are basically not equal to the radius of the concave arc structure 22. Therefore, the average alternative distance of the multiple laser points to the alternative position D is far from the radius of the concave arc structure 22, and the standard deviation of the alternative distance of the alternative position D is relatively large. It can be determined that the alternative position D is not the true center of the concave arc structure 22. In some embodiments, a standard deviation threshold can be set, and the alternative position C whose obtained alternative distance standard deviation is less than or equal to the standard deviation threshold is determined as the position of the center C of the concave arc structure 22. Those skilled in the art can set the standard deviation threshold according to actual needs, and the present disclosure does not limit this.

[0057] For another example, for each of the two alternative positions C and D of the center of the concave arc structure 22, the distance between the alternative position and each laser point in the point cloud data can be calculated, which is called the "alternative distance", and then the laser points whose alternative distances are close to the radius of the concave arc structure 22 are counted. Specifically, for example, a first distance threshold range can be set according to the radius of the concave arc structure 22, for example, the first distance threshold range is set to ±10% of the radius of the concave arc structure 22 (i.e., r±0.1r, where r is the radius of the concave arc structure 22. For example, the first distance threshold range is set to 0.9r to 1.1r, or to r to 1.1r, or to 0.9r to r). The first distance threshold range can also be set to other values, and the present disclosure does not limit this. If the alternative distance between the laser point in the point cloud data and a certain alternative position is within the first distance threshold range, the alternative distance is considered to be "close" to the radius, and the corresponding count value of the alternative position is increased by 1. For example, a counting threshold can be set, and candidate locations with count values ​​greater than or equal to the counting threshold are determined to be the true center of the concave arc structure 22. As described above, for candidate location C, the candidate distances between a considerable number of laser points in the point cloud data and it are close to the radius, resulting in a larger count value. If the count value is greater than or equal to the counting threshold, candidate location C is considered to be the true center of the concave arc structure 22. For other candidate locations (such as candidate location D), the count value is smaller. If the count value is less than the counting threshold, candidate location D is considered not to be the true center of the concave arc structure 22. Alternatively, the count values ​​of candidate locations C and D can be calculated separately, compared, and the candidate location with the larger count value is determined to be the true center of the concave arc structure 22. Thus, by calculating the count values ​​of each candidate location, the true center C of the concave arc structure 22 can be identified from the candidate locations. Those skilled in the art can set the counting threshold according to actual needs, and this disclosure does not limit this.

[0058] Through steps 310 and 320, the center C of the concave arc-shaped structure 22 in base station 20, which accommodates the autonomous mobile device 10, can be determined. This allows the approximate location of the base station to be determined, allowing the autonomous mobile device to quickly approach the base station. Because the base station's approximate location can be determined without adding additional components, circuits, or algorithms to the base station, the increased cost associated with determining the base station's location is avoided. Furthermore, the autonomous mobile device processes point cloud data obtained from the lidar during normal operation during base station search, eliminating the need for additional signal processing specifically for base station search. This saves processor computing power.

[0059] In some embodiments, in order to more accurately locate the base station, in addition to determining the position of the center C of the concave arc structure 22, the orientation of the base station 20 can also be determined, thereby determining the posture of the base station 20. The autonomous mobile device 10 can determine the exact position of the base station 20 based on the posture of the base station 20, so that the autonomous mobile device can efficiently and accurately enter the base station 20, thereby performing corresponding charging and / or cleaning tasks such as dust removal.

[0060] In some embodiments, the control method 300 for an autonomous mobile device according to the present disclosure may further include executing step 330, by the processor 18, to determine the orientation of the base station. Referring to Figure 1 , the concave arc-shaped structure 22 of the base station 20 has two parallel or coplanar end surfaces 24a and 24b at both ends. Specifically, step 330 may include sub-steps 332-336.

[0061] In sub-step 332, a first group of laser points, a second group of laser points, and a third group of laser points are identified from the point cloud data, wherein the first and second groups of laser points have the same or similar first light intensity, and the third group of laser points spaced therebetween has a second light intensity different from the first light intensity.

[0062] In this embodiment, since the two end faces 24a and 24b provided on the base station are parallel or coplanar with each other, and the two end faces 24a and 24b are close to each other relative to the distance between the base station and the autonomous mobile device, the directions and angles of the two end faces 24a and 24b relative to the autonomous mobile device 10 or the laser radar 14 are basically consistent, and the incident and reflection angles of the laser from the laser radar 14 at various locations on the two end faces 24a and 24b are basically consistent. Therefore, the reflected lasers from the two end faces 24a and 24b received by the laser radar 14, that is, the laser points used to represent the two end faces 24a and 24b in the point cloud data, have a basically consistent first light intensity.

[0063] Since the concave arc structure 22 has an arc shape different from the flat end faces 24a and 24b relative to the laser radar, its direction and angle relative to the laser radar 14 are different from the two end faces 24a and 24b. Therefore, the second light intensity of the reflected laser received by the laser radar 14 from the concave arc structure 22 is also different from the first light intensity of the reflected laser from the end face 24a or 24b, that is, the laser point representing the concave arc structure 22 in the point cloud data has a second light intensity different from the first light intensity. In other words, even if the surface materials of the end face and the concave arc structure are the same, due to the different setting positions and angles of the two end faces 24a, 24b and the concave arc structure 22, the two (the plane shape of the end face and the arc shape of the concave arc structure) will usually have different degrees of reflection of the laser, resulting in different intensities of the laser reflection rays received by the laser radar from the end face and the concave arc structure respectively, which is manifested as the first light intensity of the first and second groups of laser points corresponding to the two end faces and the second light intensity of the third group of laser points corresponding to the concave arc structure in the point cloud data obtained by the laser radar.

[0064] Furthermore, due to its curved shape within the laser plane, each location within the concave curved structure 22 has a different angle relative to the laser radar 14. This results in different intensities for the reflected laser light at each location on the concave curved structure. Consequently, the multiple laser points representing the concave curved structure 22 in the point cloud data also have different intensities. This is different from the laser points representing the flat end surfaces 24a and 24b, which have the same intensity. Therefore, the second intensity itself is not a fixed value, but rather an intensity distribution based on the position of the different laser points, which is a function of the laser point position. In one possible implementation, the point cloud data can be converted into a point map with different grayscale levels based on the reflected light intensity, and the first to third groups of laser points can be identified using a threshold segmentation algorithm, namely the OTSU algorithm. Of course, when the autonomous mobile device is far from the base station (e.g., greater than 0.5 m), the difference in intensity between the multiple laser points on the concave curved structure 22 is minimal, meaning that the constant second intensity can be used to represent the intensity of the concave curved structure 22.

[0065] In some embodiments, in order to increase the difference in light intensity of the received reflected laser light between the two end faces 24a and 24b and the concave arc-shaped structure 22, the two end faces 24a and 24b can also have the same first reflectivity (for example, a first material with a first reflectivity is coated on the end faces 24a and 24b), and the concave arc-shaped structure 22 can have a second reflectivity different from the first reflectivity (for example, a second material with a second reflectivity is coated on the concave arc-shaped structure; wherein the first reflectivity can be greater than or less than the second reflectivity) to increase the distinction between the first light intensity and the second light intensity. For example, if a material having a higher first reflectivity is coated or adhered to the surfaces of the two end surfaces 24a and 24b and a material having a lower second reflectivity is coated or adhered to the surface of the concave arc-shaped structure 22, then in step 332, the laser radar receives three groups of laser points with a "high-low-high" light intensity distribution, wherein the first and second groups of laser points show high reflectivity, while the third group of laser points in between show low reflectivity. Then, this "high-low-high" light intensity distribution can be considered to satisfy the preliminary judgment conditions and represent the two end surfaces 24a and 24b and the concave arc-shaped structure 22 in between. For another example, if the reflectivity of the two end surfaces 24a and 24b is lower and the reflectivity of the concave arc-shaped structure 22 is higher, then in step 332, the first and second groups of laser points (low reflectivity) with a "low-high-low" light intensity distribution and the third group of laser points (high reflectivity) in between can be selected.

[0066] In sub-step 334, if the first condition is met, it is determined that the first and second groups of laser points represent at least a portion of each of the two end surfaces 24a and 24b. The first condition includes: the first group of laser points can be fitted to a first straight line within the laser plane, the second group of laser points can be fitted to a second straight line within the laser plane, and the first and second straight lines have the same normal direction.

[0067] In this embodiment, in order to avoid the possibility that the laser points formed on certain environmental objects in the working area may also form point cloud data of three adjacently arranged groups of laser points with the above-mentioned light intensity characteristics (that is, the first and second groups of laser points have a first light intensity, and the third group of laser points has a second light intensity different from the first light intensity, and the first, third, and second groups of laser points are arranged adjacent to each other), it is possible to further determine whether the first and second groups of laser points actually represent at least a portion of each of the two end faces 24a and 24b, respectively.

[0068] Considering that the two end surfaces 24a and 24b are planar and have approximately the same normal direction, straight lines are used to fit the first and second groups of laser points, respectively, and the two fitted straight lines are tested to see whether they have approximately the same normal direction. Those skilled in the art will understand that the same normal direction for two straight lines means that the two straight lines also have the same direction. Therefore, if the first straight line and the second straight line have the same normal direction, then the first straight line and the second straight line must have the same direction. If the two fitted straight lines have approximately the same normal direction, then the first and second groups of laser points can be considered to represent at least a portion of each of the two parallel or coplanar end surfaces 24a and 24b.

[0069] In another possible implementation, in sub-step 334, if the second condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end faces, wherein the second condition includes: the third group of laser points can be fitted into an arc within the laser surface, and the arc can match the shape of the projection of the concave arc structure on the laser surface.

[0070] In this embodiment, if the third group of laser points can be fitted into an arc within the laser plane and the arc can match the shape of the projection of the concave arc structure 22 on the laser plane, since the two ends of the concave arc structure 22 on the base station 20 are respectively connected to two flat end surfaces 24a and 24b that are parallel or coplanar to each other, then by determining that the third group of laser points represents the concave arc structure 22, it is indirectly determined that the first and second groups of laser points adjacent to the third group of laser points in the laser plane represent at least a portion of each of the two end surfaces 24a and 24b.

[0071] After determining that the first and second groups of laser points respectively represent at least a portion of the two end surfaces 24a and 24b, if the first group of laser points can be fitted into a first straight line within the laser plane or the second group of laser points can be fitted into a second straight line within the laser plane, the process continues.

[0072] In sub-step 336, the normal direction of at least one end face, that is, the orientation of base station 20, is determined based on the first and / or second groups of laser points representing at least a portion of each of the two end faces 24a and 24b. For example, if the first condition is determined in sub-step 334, the normal directions of the two fitted lines represent the normal directions of end faces 24a and 24b. If the second condition is determined in sub-step 334, and if it is determined that the first and second groups of laser points do represent at least a portion of each of the two end faces 24a and 24b, straight lines can be fitted to the first and second groups of laser points as described above, and the normal directions of the first and second lines can be determined as the normal directions of end faces 24a and 24b, respectively. Since the normal directions of the two end faces 24a and 24b are substantially the same, in practice, the normal direction of only one of the end faces can be calculated. Simultaneously, the position of the center of the concave arc structure is determined based on the third group of laser points. Finally, the position of the base station is determined according to the position of the center of the inwardly concave arc structure and the normal direction of at least one of the end faces (ie, the orientation of the base station 20 ).

[0073] In some embodiments, if the position of the center C of the concave arc structure 22 has been obtained in step 320, the position of the center C and the known radius r of the concave arc structure 22 can be used to determine whether the third group of laser points roughly corresponds to the concave arc structure 22 in the absolute coordinate system or the relative coordinate system.

[0074] In another embodiment, if step 320 has not yet been executed, that is, the position of the center of the concave arc-shaped structure 22 has not yet been determined based on the point cloud data, then the specific method described in sub-steps 322-326 above can be applied to the third group of laser points to determine a temporary center for the third group of laser points. For example, the radius of the arc fitted by the third group of laser points can be calculated as described above and compared with the known radius r of the concave arc-shaped structure 22 to determine whether the third group of laser points can fit the concave arc-shaped structure 22. In this case, if it is determined that the third group of laser points can indeed fit the shape of the concave arc-shaped structure 22, that is, it does represent the concave arc-shaped structure 22, then the obtained temporary center can be directly determined as the center C of the concave arc-shaped structure 22.

[0075] Alternatively, a fitting circle of the third group of laser points (a circle where the arcs of the third group of laser points are equally fitted) may be obtained according to, for example, a RANSAC algorithm, and its radius may be compared with the radius r of the concave arc structure 22 . This disclosure does not impose any limitation on this.

[0076] By determining the center of the concave arc structure 22 in step 320 and the orientation of the base station 20 in step 330, the position of the base station 20 can be further determined in step 340. The processor 18 can then more accurately and efficiently guide the autonomous mobile device 10 back to the base station 20 based on the position of the base station 20.

[0077] In some embodiments, a non-volatile computer-readable storage medium or program product is also provided. The instructions contained in the computer-readable storage medium or program product can be executed on a processor to perform the above-described method for operating an autonomous mobile device. The processor includes, but is not limited to, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field-programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components.

[0078] Regarding the autonomous mobile device in the above embodiment, the specific manner in which each component performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0079] While various embodiments of the present disclosure have been described above, the above descriptions are illustrative, non-exhaustive, and not intended to be limiting of the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or improvements to existing technologies, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. An intelligent system, characterized in that: include: A base station having an inwardly concave arc structure for accommodating an autonomous mobile device, and two end faces at both ends of the inwardly concave arc structure and connected to both ends of the inwardly concave arc structure, wherein the normal directions of the two end faces are consistent with the orientation of the base station; as well as The autonomous mobile device comprises: a motion assembly configured to move the autonomous mobile device over a work surface in a work area; a laser radar configured to emit laser light to the surroundings of the autonomous mobile device within a predetermined angle range and receive reflected laser light of the laser light to obtain point cloud data, wherein the laser light forms a laser surface on a plane parallel to the working surface, a memory storing instructions; and A processor configured to invoke the instructions to perform the following steps: Obtain the point cloud data from the laser radar; Identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; If a first condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end surfaces, wherein the first condition includes: the first group of laser points can be fitted as a first straight line in the laser surface, the second group of laser points can be fitted as a second straight line in the laser surface, and the first straight line and the second straight line have the same normal direction; Determine the direction of the end face according to the first straight line and / or the second straight line, and determine the position of the center of the concave arc structure according to the third group of laser points; and The position and posture of the base station are determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

2. An intelligent system, characterized in that: include: A base station having an inwardly concave arc structure for accommodating an autonomous mobile device, and two end faces at both ends of the inwardly concave arc structure and connected to both ends of the inwardly concave arc structure, wherein the normal directions of the two end faces are consistent with the orientation of the base station; as well as The autonomous mobile device comprises: a motion assembly configured to move the autonomous mobile device over a work surface in a work area; a laser radar configured to emit laser light to the surroundings of the autonomous mobile device within a predetermined angle range and receive reflected laser light of the laser light to obtain point cloud data, wherein the laser light forms a laser surface on a plane parallel to the working surface, a memory storing instructions; and A processor configured to invoke the instructions to perform the following steps: Obtain the point cloud data from the laser radar; Identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; If the second condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end surfaces, wherein the second condition includes: the third group of laser points can be fitted into an arc within the laser surface, and the arc can match the shape of the projection of the concave arc structure on the laser surface; If the first group of laser points can be fitted into a first straight line in the laser plane or the second group of laser points can be fitted into a second straight line in the laser plane, determining the direction of the end face according to the first straight line or the second straight line, and determining the position of the center of the concave arc structure according to the third group of laser points; and The position and posture of the base station are determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

3. The intelligent system according to claim 1 or 2, characterized in that: The end surface has a first reflectivity with respect to the laser light, and the inwardly concave arc-shaped structure has a second reflectivity with respect to the laser light, the first reflectivity being different from the second reflectivity.

4. An intelligent system, characterized in that: include: A base station having a concave arc-shaped structure for accommodating an autonomous mobile device; as well as The autonomous mobile device comprises: A motion assembly configured to move the autonomous mobile device within a work area Move on the surface; A laser radar configured to emit a laser to the surroundings of the autonomous mobile device within a predetermined angle range and receive reflected light of the laser to obtain point cloud data, wherein the laser forms a laser plane on a plane parallel to the working surface; a memory storing instructions; and A processor configured to invoke the instructions to perform the following steps: Obtaining the point cloud data from the laser radar; and The position of the center of the concave arc structure is determined according to the point cloud data.

5. The intelligent system according to claim 4, characterized in that: The base station has two end faces at both ends of the inwardly concave arc structure, which are respectively connected to the two ends of the inwardly concave arc structure, and the normal directions of the two end faces are consistent with the orientation of the base station. The processor is further configured to invoke the instructions to perform the following steps: identifying, in the working area, at least a portion of each of the two end surfaces based on the point cloud data; determining a normal direction of at least one of the two end surfaces based on at least a portion of each of the two end surfaces; Determining the orientation of the base station according to the normal direction; as well as The position and posture of the base station are determined according to the position of the center of the inwardly concave arc structure and the orientation of the base station.

6. A control method for an autonomous mobile device, characterized in that: The autonomous mobile device is an autonomous mobile device in the intelligent system according to claim 1 or 3, and the control method comprises: Obtain the point cloud data from the laser radar; Identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; If the first condition is met, it is determined that the first group of laser points and the second group of laser points represent at least a portion of each of the two end surfaces, wherein the first condition includes: the first group of laser points can be fitted as a first straight line in the laser surface, the second group of laser points can be fitted as a second straight line in the laser surface, and the first straight line and the second straight line have the same normal. direction; determining the direction of the end surface according to the first straight line and / or the second straight line, and determining the position of the center of the concave arc structure according to the third group of laser points; and The position and posture of the base station are determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

7. A control method for an autonomous mobile device, characterized in that: The autonomous mobile device is an autonomous mobile device in the intelligent system according to claim 2 or 3, and the control method comprises: Obtain the point cloud data from the laser radar; Identifying a first group of laser points, a second group of laser points, and a third group of laser points from the point cloud data, wherein the first group of laser points and the second group of laser points have a first light intensity, and the third group of laser points is located between the first group of laser points and the second group of laser points and has a second light intensity different from the first light intensity; If the second condition is met, it is determined that the first group of laser points and the second group of laser points respectively represent at least a portion of each of the two end surfaces, wherein the second condition includes: the third group of laser points can be fitted into an arc within the laser surface, and the arc can match the shape of the projection of the concave arc structure on the laser surface; If the first group of laser points can be fitted into a first straight line in the laser plane or the second group of laser points can be fitted into a second straight line in the laser plane, determining the direction of the end face according to the first straight line or the second straight line, and determining the position of the center of the concave arc structure according to the third group of laser points; and The position and posture of the base station are determined according to the position of the center of the concave arc structure and the normal direction of at least one of the end faces.

8. A control method for an autonomous mobile device, characterized in that: The autonomous mobile device is an autonomous mobile device in the intelligent system according to claim 4, and the control method comprises: Obtaining the point cloud data from the laser radar; and The position of the center of the concave arc structure is determined according to the point cloud data.

9. The control method according to claim 8, characterized in that: The base station has two end faces at both ends of the inwardly concave arc structure, which are respectively connected to the two ends of the inwardly concave arc structure, and the normal directions of the two end faces are consistent with the orientation of the base station. The control method further comprises: identifying, in the working area, at least a portion of each of the two end surfaces based on the point cloud data; determining a normal direction of at least one of the two end surfaces based on at least a portion of each of the two end surfaces; determining the orientation of the base station according to the normal direction; and The position and posture of the base station are determined according to the position of the center of the inwardly concave arc structure and the orientation of the base station.

10. The control method according to claim 8 or 9, characterized in that: The step of determining the position of the center of the concave arc structure according to the point cloud data comprises: Taking the position of each laser point in the point cloud data as the center of the construction circle and the radius of the concave arc structure as the radius, a plurality of construction circles are constructed, wherein each of the plurality of construction circles includes at least a partial arc; Obtaining the position of the intersection point of each pair of intersecting construction circles among the plurality of construction circles; and The position of the center of the concave arc structure is determined according to the position of the intersection point.

11. The control method according to claim 10, characterized in that: The partial arc is located within the working area, and the intersection point is on the partial arc.

12. The control method according to claim 10, characterized in that: The step of determining the position of the center of the concave arc structure according to the point cloud data comprises: The obtained set of multiple intersection points is used as an intersection point set; For the position of each intersection point in the working area, calculate the number of intersection points in the intersection point set that fall at the position of each intersection point in the working area; and The intersection position with the largest number of intersection points is determined as the position of the center of the inwardly concave arc structure.

13. The control method according to claim 10, characterized in that: The step of determining the position of the center of the concave arc structure according to the point cloud data comprises: The obtained set of multiple intersection points is used as an intersection point set; Clustering the set of intersection points into at least two intersection point subsets; and Determine the centroid position of each of the at least two intersection point subsets as a candidate position of the center of the inward concave arc structure; For each candidate position, calculate the distance between each laser point in the point cloud data and the candidate position An alternative distance between the two positions is determined, and according to the alternative distance and the radius of the inwardly concave arc-shaped structure, it is determined whether the alternative position is the position of the center of the inwardly concave arc-shaped structure.

14. The control method according to claim 13, characterized in that: Clustering the intersection point set into at least two intersection point subsets includes: clustering the intersection point set into at least two intersection point subsets by using a K-means method.

15. The control method according to claim 13, characterized in that: The step of judging whether the candidate position is the position of the center of the concave arc structure according to the candidate distance and the radius of the concave arc structure includes: For each of the alternative positions, an average alternative distance is calculated based on multiple alternative distances, and a standard deviation of the alternative distance is calculated based on multiple alternative distances and the average alternative distance. If the standard deviation of the alternative distance is less than or equal to a standard deviation threshold, it is determined that the alternative position is the position of the center of the concave arc structure.

16. The control method according to claim 13, characterized in that: The step of judging whether the candidate position is the center of the concave arc structure according to the candidate distance and the radius of the concave arc structure comprises: For each laser point, the number of laser points within the candidate distance within the first distance threshold range is counted, and if the count is greater than or equal to the counting threshold, it is determined that the candidate position is the position of the center of the inwardly concave arc structure.

17. The control method according to any one of claims 6 to 9, characterized in that: Also includes: The autonomous mobile device is controlled to move toward the base station according to the position of the base station.

18. A computer-readable storage medium, characterized in that: The storage medium stores a computer program including instructions, which, when executed by a processor of an autonomous mobile device, implement the control method according to any one of claims 6 to 17.

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