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

Abstract

The invention relates to an intelligent system, a control method of an autonomous mobile device, and a storage medium. The intelligent system comprises a base station with an inwards-concave arc-shaped structure used for containing the autonomous mobile device and the autonomous mobile device, the two ends of the inwards-concave arc-shaped structure are connected with two end faces respectively, and the normal directions of the two end faces are consistent with the orientation of the base station. The autonomous mobile device is used for obtaining 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 representing two end faces and the concave arc-shaped structure from the point cloud data, determining the direction of the end faces according to a first straight line and / or a second straight line, and determining the position of the circle center of the concave arc-shaped structure according to the third group of laser points. And determining the pose of the base station according to the position of the circle center of the concave arc-shaped structure and the normal direction of the end face. Therefore, the autonomous mobile device can determine the pose of the base station with low cost and computing power requirements so as to drive into the base station.

Description

Technical Field

[0001] The present disclosure relates to the field of smart home technology, and in particular to a smart system, a control method for an autonomous mobile device, and a storage medium. Background Art

[0002] With the continuous development of autonomous mobile device technology, intelligent systems with various purposes have emerged. The intelligent system includes an autonomous mobile device and a base station that matches it. The autonomous mobile device can move on the working surface of the work area to complete specific tasks (such as cleaning, item delivery, and patrolling, etc.). To this end, the autonomous mobile device needs to obtain a map of the work area and determine the position and posture of the autonomous mobile device itself. Common methods for creating maps and determining postures include simultaneous localization and mapping (SLAM) technology.

[0003] In the technology of laser SLAM, a mechanical laser radar (hereinafter referred to as 360-degree laser radar) installed on an autonomous mobile device for 360-degree rotation 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 a rotation axis perpendicular to the ground, it scans and emits lasers around in the horizontal plane and receives reflected lasers reflected by objects in the working area (hereinafter referred to as environmental objects), so that multiple laser points representing environmental objects at corresponding angles and distances in the working area can be detected and constitute a "point cloud"; the laser radar continuously rotates 360 degrees at a certain frequency, and each rotation can obtain a series of laser points reflected by surrounding environmental objects. All these laser points generally represent the contour of the corresponding environmental objects 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, etc.).

[0004] The base station of the intelligent system provides auxiliary functions such as charging, docking and even cleaning of autonomous mobile devices. For example, when the autonomous mobile device completes the cleaning task or the battery is low, it needs to return to the base station for charging and other operations; and the autonomous mobile device will usually dock at the base station when not performing a task, waiting to perform the next task. Usually, the autonomous mobile device needs to accurately and autonomously drive to a specific location in the base station. For example, if charging is required, the autonomous mobile device needs to accurately align its charging contacts with the charging contacts on the base station when entering the base station for charging.

[0005] Therefore, in order for the autonomous mobile device to accurately and autonomously drive to such a specific position in the base station, the autonomous mobile device needs to locate such a specific position in the base station (i.e., determine the posture of the base station, including the position and orientation of the base station). Some prior arts provide that the base station sends out a guidance signal and the receiver on the autonomous mobile device receives the guidance signal to determine the posture of the base station; some prior arts use image sensors (such as cameras) to capture specific image features pasted or set at a specific position of the base station to determine the posture of the base station. However, these solutions require additional hardware equipment on the one hand, thereby increasing the cost; on the other hand, these solutions require processing of additional signals, which increases the computational effort of the processor. Summary of the invention

[0006] 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.

[0007] 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 respectively 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 comprises: a motion component configured to move the autonomous mobile device on a working surface in a working area; a laser radar configured to emit a laser to the surroundings of the autonomous mobile device within a predetermined angle range, and receive reflected laser light of the laser to obtain point cloud data, wherein the laser 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 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 satisfied, 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.

[0008] 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 respectively 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 a laser to the surroundings of the autonomous mobile device within a predetermined angle range, and receive reflected laser light of the laser to obtain point cloud data, wherein the laser 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 judged 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 in 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 in the laser surface or the second group of laser points can be fitted as a second straight line in 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.

[0009] 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 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 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 according to the point cloud data.

[0010] In a fourth 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 an intelligent system according to the first aspect, 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 first condition is satisfied, 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 comprises: 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 face 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 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.

[0011] 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, 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 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.

[0012] In the sixth aspect of the present disclosure, a control method for an autonomous mobile device is provided. The autonomous mobile device is an autonomous mobile device in the intelligent system according to the third aspect above. 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 according to the point cloud data.

[0013] 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.

[0014] According to the technical solution disclosed in the present invention, the autonomous mobile device determines 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, thereby determining the approximate position of the base station, so that the autonomous mobile device can quickly approach the base station. Since the approximate position of the base station can be determined without adding additional devices, circuits, and algorithms to the base station, the increase in cost caused by determining the position of the base station can be avoided, and the autonomous mobile device processes the point cloud data obtained from the laser radar during the process of searching for the base station, which should be processed during normal operation, so there is no need to process additional signals specifically for searching for the base station, thereby saving the computing power of the processor.

[0015] 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 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.

[0016] 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

[0017] 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.

[0018] Figure 1 A schematic diagram of an intelligent system according to an exemplary embodiment is shown.

[0019] Figure 2 A schematic diagram illustrating point cloud data according to an exemplary embodiment.

[0020] Figure 3A flow chart illustrating a control method of an autonomous mobile device according to an exemplary embodiment.

[0021] Figure 4 A schematic diagram showing positioning of the center of a concave arc-shaped structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] 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 specified.

[0023] 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.

[0024] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0025] Figure 1 FIG. 1 is a schematic diagram showing an intelligent system according to an exemplary embodiment. Figure 1 , the intelligent system may include an autonomous mobile device 10 and a base station 20, wherein the autonomous mobile device 10 is driving back to the base station 20. It should be understood that, in the case where the autonomous mobile device 10 needs to return to the base station 20, for example, the autonomous mobile device 10 needs to be charged and / or cleaned, the autonomous mobile device 10 can drive back to the base station 20. Accordingly, in the case where the autonomous mobile device 10 needs to leave the base station 20, for example, the autonomous mobile device 10 needs to perform a task on the working surface of the working area, the autonomous mobile device 10 can drive out of the base station 20.

[0026] The base station 20 has a concave arc-shaped structure 22, which is used to accommodate the autonomous mobile device 10 that drives back to the base station 20, wherein the concave arc-shaped structure 22 has a determined and known radius and center (referred to as the center of the concave arc structure in this disclosure). Figure 1 In this embodiment, the concave arc structure 22 is a symmetrical structure having a symmetry axis (ie, Figure 1 In the present disclosure, the orientation of the base station 20 refers to a direction from the inwardly concave arc-shaped structure 22 to the center of the inwardly concave arc-shaped structure 22 along the symmetry axis of the inwardly concave arc-shaped structure 22.

[0027] In some embodiments, see Figure 1The base station 20 has two end faces 24a and 24b at both ends of the concave arc structure 22 and connected to the two ends of the concave arc structure 22, and the end faces 24a and 24b are substantially parallel or coplanar. In an exemplary embodiment, the two end faces 24a and 24b are perpendicular to the ground, and the normal directions of the two end faces 24a and 24b (i.e., the directions perpendicular to the end faces) are substantially consistent with the orientation of the base station 20. In practice, there may be a certain tolerance (such as ±5°) between the normal directions of the two end faces 24a and 24b, which also means that the end faces 24a and 24b are substantially parallel or coplanar; there may also be a certain tolerance (such as ±5°) between the normal directions of each end face 24a and 24b and the orientation of the base station 20, which also means that the normal directions of each end face 24a and 24b are substantially consistent with the orientation of the base station 20.

[0028] Since the position where the front or rear contour of the autonomous mobile device 10 meets the concave arc-shaped structure 22 at the front end of the base station 20 is usually an arc-shaped outer contour, when the autonomous mobile device 10 is normally parked at the base station 20, the arc-shaped outer contour of the autonomous mobile device 10 can enter the concave arc-shaped structure of the base station 20 and match it. Therefore, as long as the autonomous mobile device 10 obtains the position and orientation of the base station 20 (the two are collectively referred to as posture), it can move toward the base station 20 and finally accurately park at a specific position of the base station 20. For example, Figure 1 As shown, two charging contacts are usually symmetrically arranged at the front end of the base station 20, and the connection direction of the two charging contacts is usually perpendicular to the direction 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 are docked with the charging contacts of the base station 20, so that the base station 20 charges the autonomous mobile device 10.

[0029] The autonomous mobile device 10 may include a motion component 12, which is used to enable the autonomous mobile device 10 to move on a work surface in a work area. The autonomous mobile device 10 may also include a memory 16, which stores instructions. The autonomous mobile device 10 may also include a processor 18, which is used to call the instructions in the memory 16 to execute the steps to be described below, thereby controlling the components of the autonomous mobile device 10 to perform corresponding operations.

[0030] 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) to the surrounding environment. The reflected light of the laser beam emitted by the laser radar 14 after being reflected by the environmental objects can be received by the laser radar 14. The distance data between the autonomous mobile device 10 and the environmental objects can be calculated based on the emitted laser light and the received reflected laser light. The "point" formed by the laser beam emitted by the laser radar on the environmental objects is received by the laser radar, which is referred to as a laser point in the present disclosure.

[0031] 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 emission 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 ranging method, etc., 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, for example. This disclosure does not make specific restrictions on this.

[0032] 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 limit 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 rotation axis of the laser radar, and the surface scanned 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 rotation axis of the rotating mirror is the laser surface; and for a non-rotating pure solid-state laser radar, the surface perpendicular to the transmitting or receiving array (surface array) of the solid-state laser radar and parallel to the working surface is the laser surface. In an exemplary embodiment, on the laser surface, the laser point formed after the laser emitted by the laser radar 14 irradiates the environmental object is received by the laser radar, thereby obtaining 2D (two-dimensional) point cloud data within the laser surface. In such as Figure 1 When the rear of the base station 20 is placed against the wall, the laser radar 14 can obtain the following information: Figure 2 The 2D point cloud data shown includes laser points representing the concave arc structure 22 (eg Figure 2 The dashed area A in the figure) and the laser points on the two walls (e.g. Figure 2In the present disclosure, for the convenience of description, even if a 3D 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 is converted into 2D point cloud data within the laser surface during the description process.

[0033] It should be understood that for the sake of simplicity, Figure 1 Only some components of the autonomous mobile device 10 and the base station 20 included in the intelligent system are shown in the figure. However, other components may be included in the autonomous mobile device 10 and the base station 20 according to the design and / or application requirements. In other words, the autonomous mobile device 10 and the base station 20 may also include other components for realizing their functions. In an exemplary embodiment, the autonomous mobile device 10 is a cleaning robot, and the cleaning robot includes a brush head or a mop plate for cleaning and a dust box for storing garbage. The autonomous mobile device 10 may also include a charging contact for charging; some models of the autonomous mobile device 10 may also include a dust box movable cover for communicating with the inside of the dust box. The base station 20 may also include a dust box interface corresponding to the dust box movable cover on the autonomous mobile device 10, so that when the autonomous mobile device 10 enters the base station 20 and its arc-shaped outer contour corresponds to the concave arc-shaped structure 22 of the base station 20, the charging contacts and the dust box movable cover on the autonomous mobile device 10 are respectively docked with the charging contacts and the dust box interface on the base station 20, thereby realizing the functions of charging and emptying the dust box.

[0034] In order for the autonomous mobile device 10 to drive into 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 orientation of the concave arc-shaped structure 22. To this end, the processor 18 of the autonomous mobile device 10 can execute the following Figure 3 The method shown.

[0035] Figure 3A flow chart of a control method of an autonomous mobile device according to an exemplary embodiment is shown. The control method 300 executed by the processor 18 by calling instructions in the memory 16 includes: step 310, the processor 18 obtains point cloud data from the laser radar 14; and step 320, the processor 18 determines the position of the center of the concave arc structure 22 according to the point cloud data, and since the position of the center of the concave arc structure 22 is very close to the actual position of the base station 20 (only a distance of the radius of the concave arc structure 22), the position of the base station 20 can be roughly determined according to the position of the center. In some exemplary embodiments, the autonomous mobile device 10 can move according to the position of the center of the concave arc structure 22 (i.e., the rough position of the base station 20), and after approaching the rough position of the base station 20, it is precisely aligned with the base station 20 according to, for example, receiving a guidance signal sent by the base station 20, so that the autonomous mobile device 10 can enter and accurately dock on the base station 20.

[0036] 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 according to the point cloud data; and step 340, determining the posture of the base station 20 according to 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 drive into the base station 20.

[0037] 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 contours of objects in the working area within the laser plane scanned by the laser radar 14.

[0038] In an exemplary embodiment, the laser radar 14 has a predetermined detection distance range, that is, the laser reflected by the objects within the detection distance range in the working area will be used by the laser radar 14 to form point cloud data, while the laser reflected by the objects beyond 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 the laser points in the 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 the laser reflected by the 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, so as 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 the present disclosure does not limit this.

[0039] When the autonomous mobile device 10 is within the predetermined detection distance of the base station 20, the laser emitted by the laser radar 14 will irradiate the concave arc structure 22, the end faces 24a, 24b, and other environmental objects such as surrounding walls or furniture of the base station 20, and obtain the following Figure 2 It can be seen that such point cloud data includes laser points representing the concave arc structure 22, end faces 24a, 24b, and surrounding walls or furniture, that is, the laser points reflected by the concave arc structure 22, end faces 24a, 24b, and surrounding walls or furniture constitute a part of the point cloud data.

[0040] 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, namely, 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 laser radar 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 other embodiments, each laser point in the point cloud data can have relative coordinates relative to the autonomous mobile device 10 (such as using the position of the autonomous mobile device 10 as the origin of the relative coordinate system).

[0041] In step 320, the position of the center of the concave arc-shaped structure 22 can be obtained according to the point cloud data. Specifically, in an exemplary embodiment, step 320 includes sub-steps 322-326. In sub-step 322, the position of each laser point in the point cloud data is used as the center of the construction circle, and the radius of the concave arc-shaped structure 22 is used as the radius of the construction circle to construct a plurality of construction circles, wherein each construction circle includes at least a portion of the arc; as described above, the radius of the concave arc-shaped structure 22 is known.

[0042] Figure 4 A schematic diagram showing the position of the center of the concave arc structure according to an exemplary embodiment is shown, wherein the Figure 2 An example of multiple constructed circles obtained after executing sub-step 322 for the laser points in the point cloud data. Figure 4 Only the construction circles obtained based on some laser points in the point cloud data are shown as examples. For example, in order to reduce the computational burden, only laser points within the laser radar detection distance range may be used to form the construction circles, but it is understandable that other criteria may be used to select some laser points in the point cloud data to form the construction circles, or all laser points in the point cloud data may be used to form all the construction circles.

[0043] In sub-step 324, for each pair of intersecting construction circles in the obtained construction circles, the position of their intersection is obtained. Whether each pair of construction circles intersects and the intersection of the two construction circles when they intersect can be calculated by combining equations of multiple construction circles in the coordinate system; the intersection can also be obtained by image processing methods such as contour extraction (for example, contours are extracted from an image containing multiple construction circles, and the pixel points belonging to the two contours obtained from each pair of intersecting contours are the intersection points). Figure 4 As shown, every two intersecting construction circles have one or two intersection points.

[0044] In sub-step 326, the position of the center C of the concave arc-shaped structure 22 is determined according to the intersection point obtained in the above steps.

[0045] Since the laser points on the concave arc structure 22 are located on the same circle, that is, the circumference of the circle where the concave arc structure 22 is located, the construction circles obtained with the laser points on the concave arc structure 22 as the center of the circle intersect at least at the center C of the concave arc structure 22. In other words, if the two construction circles obtained according to the two laser points on the concave arc structure 22 have only one intersection point, then the intersection point is the center C of the concave arc structure 22; if it has two intersection points, then one of them is the center C of the concave arc structure 22, and the other intersection point is on the other side of the concave arc structure 22 (equivalent to the space behind the base station), which does not belong to the position that the autonomous mobile device 10 is expected to reach. In some embodiments, certain constraints are applied when creating the construction circle, so that the center C representing the concave arc structure can be easily and accurately found through the intersection of the construction 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 within the map.

[0046] In some embodiments, Figure 4As shown, multiple intersecting construction circles can be obtained according to the laser points in the point cloud data, and each construction circle intersects with at least one other construction circle and generates at least one intersection point, thereby obtaining many intersection points. However, these laser points used to create construction circles may be located on the concave arc structure 22, or may correspond to other objects, such as the above-mentioned contact sheet and interface, the surrounding walls, and the end faces 24a, 24b, so the intersection point of any two intersecting construction circles may or may not be the center C of the concave arc structure 22. In order to find the position of the center C of the concave arc structure 22 based on such many intersection points, in some embodiments, sub-step 326 also includes detailed steps 3261 to 3263. In 3261, the set of multiple intersection points is processed as an intersection point set, and the position of the center C of the concave arc structure 22 is determined according to the intersection point set in 3262 and 3263.

[0047] In detailed step 3261, the coordinates of each intersection point in the intersection point set may be recorded in an absolute coordinate system or a relative coordinate system. Figure 4 As shown, if the construction circles generated by the laser points on the concave arc structure 22 intersect, according to geometric knowledge, there should be at least an intersection point at the center C of the concave arc structure 22, so there will be many intersection points in the intersection point set located at the center C of the concave arc structure 22, while the intersection points not near the center C of the concave arc structure 22 will not be so concentrated. In an exemplary embodiment, the position of the center C of the concave arc structure 22 can be determined by finding the position or area where the intersection points between the construction circles are most densely populated.

[0048] Specifically, in the detailed step 3262, the number of intersections at the positions of each intersection in the intersection set falling within the working area is calculated, and then the intersection position 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 correspond to the corresponding grid of the map and be represented by the position of the grid, so the intersection position can be represented by the position of the grid where the intersection is located. If multiple intersections fall in 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 same intersection position of these intersections (i.e., the area covered by the grid represents the position of the intersection to increase the count of intersections in the adjacent area). The number of grids and the size of the grids (i.e., the size of the area covered by each grid) can be determined according to the image resolution, wherein the number of grids and the size of the grids can be determined by those skilled in the art according to actual needs, and the present disclosure does not limit this.

[0049] In other embodiments, the absolute or relative coordinates of the intersections may also 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 size of the predetermined distance threshold may be determined by a person skilled in the art according to actual needs, and the present disclosure does not limit this. In this way, 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 in the common or adjacent region of these intersections) may be used as the position of the center C of the concave arc structure 22.

[0050] Alternatively, in the detailed step 3263, the intersection set can be clustered into several subsets by a clustering algorithm and the centroid position of each subset can be calculated as the position of the center C of the concave arc structure 22, and the correct position of the center C of the concave arc structure 22 can be identified therefrom. For example, the clustering of the intersection set can be realized by a K-means algorithm, or other algorithms can be used to cluster the intersection set, which is not limited in the present disclosure.

[0051] 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 other subsets 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.

[0052] In the implementation using the K-means algorithm, then (ii) 2 points are randomly selected from the intersection set as centroids; (iii) for each intersection in the intersection set, the distance between it and each centroid in the two centroids is calculated, and the intersection is assigned to the subset corresponding to the centroid with a closer distance; (iv) after all the intersections 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 means 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 to be accurate, thereby terminating the clustering operation and placing the two centroid positions ( Figure 4C and D in FIG. 2 are used as candidate positions of 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.

[0053] Next, it is necessary to identify the position of the true center C of the concave arc structure 22 from the two candidate positions C and D of 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 position C is basically equal to the known radius of the concave arc structure 22. For another candidate position D, there may be only a few laser points in the point cloud data whose distances from the candidate position D coincidentally equal to the radius of the concave arc structure 22. Therefore, the position of the true center C of the concave arc structure 22 can be identified from the candidate positions C and D by respectively calculating the distances between the candidate positions C and D and each laser point in the point cloud data.

[0054] 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 calculation burden and improve the 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. i The 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, after obtaining the average candidate distance l of the candidate position 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 The average distance to the alternative 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 real 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 real alternative position can be determined based on this. For example, for the real alternative position C, since the alternative distances between the laser point on the concave arc structure 22 in the point cloud data and the real 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 real alternative position C is relatively small. Therefore, it can be determined that the alternative position C is the real center of the concave arc structure 22. As for another false alternative position D (the alternative position D is only a mathematical solution, but it is impossible in the actual working area, so it should be eliminated), the alternative distances between the multiple laser points in the point cloud data and the alternative position D are basically not equal to the radius of the concave arc structure 22. Therefore, the average alternative distance from 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 standard deviation of the alternative distance 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.

[0055] 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, the 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 the radius of the concave arc structure 22 ±10% (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 may be set, and the candidate position whose count value is greater than or equal to the counting threshold is determined as the position of the true center of the concave arc structure 22. As described above, for the candidate position C, a considerable portion of the laser points in the point cloud data have an alternative distance close to the radius, so the count value is large. If the count value is greater than or equal to the counting threshold, the candidate position C is considered to be the true center of the concave arc structure 22. For other candidate positions (such as the candidate position D), the count value is small. If the count value is less than the counting threshold, the candidate position D is considered not to be the true center of the concave arc structure 22. The count values ​​of the candidate positions C and D may also be calculated separately, and the two may be compared, and the candidate position with the larger count value may be used as the true center of the concave arc structure 22. It can be seen that the position of the true center C of the concave arc structure 22 can be identified from the candidate positions by calculating the count values ​​of each candidate position. Those skilled in the art can set the counting threshold according to actual needs, and the present disclosure does not limit this.

[0056] Through steps 310 and 320, the position of the center C of the concave arc structure 22 in the base station 20 for accommodating the autonomous mobile device 10 can be obtained, thereby determining the approximate position of the base station, so that the autonomous mobile device can quickly approach the base station. Since the approximate position of the base station can be determined without adding additional devices, circuits, and algorithms to the base station, the increase in cost caused by determining the position of the base station can be avoided, and the autonomous mobile device processes the point cloud data obtained from the laser radar during the process of searching for the base station, which should be processed during normal operation, so there is no need to process additional signals specifically for searching for the base station, thereby saving the computing power of the processor.

[0057] 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.

[0058] In some embodiments, the control method 300 of the 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. Figure 1 The two ends of the concave arc structure 22 of the base station 20 have two end surfaces 24a and 24b that are parallel or coplanar to each other. Specifically, step 330 may include sub-steps 332-336.

[0059] 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, 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.

[0060] 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.

[0061] 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 faces 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 settings 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, which is manifested in the point cloud data obtained by the laser radar, 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 are different.

[0062] In addition, for each part of the concave arc structure 22, due to its arc shape in the laser plane, each part has a different angle relative to the laser radar 14, so that the light intensity of the reflected laser at each part of the concave arc structure is also different, so that the light intensity of the multiple laser points representing the concave arc structure 22 in the point cloud data is also different from each other, which is different from the same light intensity of the laser points representing the flat end faces 24a and 24b. Therefore, the second light intensity itself is not a fixed value, but a light intensity distribution based on different laser point positions, and the light intensity distribution is a function of the laser point position. In a possible implementation, the point cloud data can be converted into a point map with different gray levels according to the light intensity of the reflected light, and the threshold segmentation algorithm, namely the OTSU algorithm, is used to identify the first to third groups of laser points. Of course, when the autonomous mobile device is far away from the base station (for example, greater than 0.5m), the difference in light intensity between the multiple laser points on the concave arc structure 22 is very small, that is, the light intensity of the concave arc structure 22 can be represented by a constant second light intensity.

[0063] In some embodiments, in order to increase the difference in light intensity of the received reflected laser 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, a material having a higher first reflectivity is coated or pasted on the surfaces of the two end faces 24a and 24b, and a material having a lower second reflectivity is coated or pasted on the surface of the concave arc-shaped structure 22. 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, and the third group of laser points in the middle show low reflectivity. The "high-low-high" light intensity distribution can be regarded as satisfying the preliminary judgment condition to represent the two end faces 24a and 24b and the concave arc-shaped structure 22 in the middle. For another example, if the reflectivity of the two end faces 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 the middle can be selected.

[0064] 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 as a first straight line in the laser plane, the second group of laser points can be fitted as a second straight line in the laser plane, and the first straight line and the second straight line have the same normal direction.

[0065] 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 having 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 can be further determined whether the first and second groups of laser points do indeed represent at least a portion of each of the two end surfaces 24a and 24b, respectively.

[0066] Considering that the two end faces 24a and 24b are planes and have substantially the same normal direction, a straight line is used to fit the first and second groups of laser points respectively, and it is checked whether the two fitted straight lines have substantially the same normal direction. A person skilled in the art should know that the same normal direction of two straight lines means that the directions of the two straight lines are also the same. Therefore, if the first straight line and the second straight line have the same normal direction, the first straight line and the second straight line must have the same direction. If the two fitted straight lines have substantially the same normal direction, it can be considered that the first and second groups of laser points represent at least a portion of each of the two end faces 24a and 24b that are parallel or coplanar to each other.

[0067] 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.

[0068] 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.

[0069] After determining that the first and second groups of laser spots represent at least a portion of each of the two end surfaces 24a and 24b, if the first group of laser spots can be fitted as a first straight line in the laser plane or the second group of laser spots can be fitted as a second straight line in the laser plane, the process continues.

[0070] In sub-step 336, the normal direction of at least one end face, that is, the orientation of the 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 fitting straight lines represent the normal directions of the end faces 24a and 24b; if the second condition is determined in sub-step 334, then in the case where 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, the first and second groups of laser points can be fitted with straight lines as described above, and the normal directions of the first and second straight lines can be determined as the normal directions of the end faces 24a and 24b, respectively. Since the normal directions of the two end faces 24a and 24b are substantially the same, in practice, only the normal direction of any one of the end faces can be calculated. At the same time, the position of the center of the concave arc structure is determined based on the third group of laser points. Finally, the position and posture 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 ).

[0071] 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 an absolute coordinate system or a relative coordinate system.

[0072] In another embodiment, if step 320 has not been executed at this time, that is, the position of the center of the concave arc structure 22 has not been determined according to the point cloud data, then the specific method of the above sub-steps 322-326 can be applied to the third group of laser points to determine the temporary center of the third group of laser points, such as calculating the radius of the arc fitted by the third group of laser points as described above and comparing it with the known radius r of the concave arc structure 22 to determine whether the third group of laser points can fit the concave arc 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 structure 22, that is, it does represent the concave arc structure 22, then the obtained temporary center of the circle can be directly determined as the center C of the concave arc structure 22.

[0073] The fitting circle of the third group of laser points (the circle where the arc of the third group of laser points is fitted equally) can also be obtained according to, for example, the RANSAC algorithm, and its radius can be compared with the radius r of the concave arc structure 22, which is not limited in the present disclosure.

[0074] By determining the position of the center of the concave arc structure 22 in step 320 and determining the orientation of the base station 20 in step 330, the posture of the base station 20 can be further determined in step 340. The processor 18 can then make the autonomous mobile device 10 return to the base station 20 more accurately and efficiently according to the posture of the base station 20.

[0075] In some embodiments, a non-volatile computer-readable storage medium or program product is also provided, and the instructions included in the computer-readable storage medium or program product can be executed on a processor to perform the above-mentioned 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.

[0076] 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.

[0077] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill 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 over a work surface in a work area; 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 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; 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, a candidate distance between each laser point in the point cloud data and the candidate position is calculated, and whether the candidate position is the position of the center of the concave arc structure is determined according to the candidate distance and the radius of the concave arc 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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