Side-looking laser-based along-wall distance measurement method and apparatus

Abstract

A wall-following distance measurement method based on side-view line laser, comprising: emitting a vertical line laser to the left or right side of a mobile robot, and resolving a return signal into a point set with distance information; plotting the point set in a coordinate system according to the distance information; fitting the distance information of the point set, and determining whether the points in the point set can be fitted into a complete ground surface by verifying the change speed of the distance information of adjacent points in the point set; when the points in the point set cannot be fitted into a complete ground surface, measuring the height of an obstacle and the distance between the obstacle and the mobile robot; and determining the actual distance between the obstacle and the mobile robot according to the distance information of the center of the obstacle to the mobile robot and the inclination angle of the plane where the line laser is located to the ground. The scheme has less number of operations and less single operation amount.

Description

Technical Field

[0001] This application relates to the field of robot obstacle detection technology, and in particular to a method and apparatus for forward-looking laser obstacle recognition for mobile robots. Background Technology

[0002] Mobile robots need to identify surrounding obstacles during movement in order to avoid obstacles and plan and navigate cleaning paths. Existing obstacle detection methods are usually based on technologies such as infrared sensors, ultrasonic sensors, radar, and visual recognition. Among them, infrared sensors are easily interfered with, and the requirements for detection accuracy are getting higher and higher as products are updated. On this basis, ultrasonic sensors, radar, and visual recognition can provide higher detection accuracy, but these methods have more complex software and higher requirements for hardware. Existing solutions for robot obstacle detection use line lasers, but they usually need to introduce grid distance calculation to determine the distance parameters between grids, and then introduce density algorithms to cluster obstacle points to find obstacles. This has a large amount of computation and requires better storage and computing units.

[0003] CN114543725A discloses a laser calibration method, apparatus, device, and storage medium. This method calibrates the distance and angle of the reflected laser by fitting the laser to a reference coordinate system. Based on this coordinate system, the method can calculate the distance between the laser point and the laser transceiver, as well as the angle between the emitted laser and the horizontal plane. Building upon this, it is necessary to propose an obstacle ranging method that utilizes various detectable data to calculate the distance to obstacles with low computational complexity. Summary of the Invention

[0004] The purpose of this application is to propose a method for finding obstacles based on single-line laser detection and clustering, so as to reduce the computational load of line laser obstacle detection.

[0005] To address the aforementioned technical problems, this application provides a method for measuring wall distance based on side-line laser, employing the following technical solution:

[0006] The wall-side distance measurement method based on side-line laser includes the following steps:

[0007] A vertical laser beam is emitted to the left or right of the mobile robot, and the returned signal is parsed into a set of points with distance information; the plane in which the set of points formed by the laser beam is located is perpendicular to the horizontal plane, and;

[0008] The point set is plotted in the coordinate system based on the distance information;

[0009] The distance information of the point set is fitted to obtain the intercept of the change in distance information of adjacent points in the point set; and the points in the point set are fitted to a complete ground by verifying whether the rate of change of distance information of adjacent points in the point set conforms to the intercept.

[0010] When the points in the point set cannot be fitted to a complete ground, the points whose distance information is within a preset range are clustered according to the distance information of the points in the point set; several clusters are obtained, wherein the proportion of the points in the cluster whose height difference between the height and the ground height is less than a distance threshold exceeds a proportion threshold, then the cluster is a ground cluster; the cluster in which the height difference between the height and the ground height of the points exceeds a preset value is an obstacle cluster.

[0011] The method of determining whether an obstacle is a vertical surface is used. The method extracts the ground cluster and the obstacle cluster with the highest point height. When the points in the obstacle cluster can be fitted to a straight line, and the straight line is perpendicular to the straight line fitted to the points in the ground cluster in the coordinate system, the obstacle is determined to be a vertical surface obstacle.

[0012] Alternatively, a cylindrical surface can be used to determine whether an obstacle is considered an obstacle. The cylindrical surface determination method extracts the obstacle cluster with the highest point. When there are adjacent points in the obstacle cluster with increasing height and increasing horizontal distance from the mobile robot, the obstacle is determined to be an obstacle with a cylindrical surface.

[0013] When the surface of the obstacle is flat, or when the obstacle is considered to be a cylindrical surface, the height of the obstacle and the distance between it and the mobile robot are calculated by using a detection method corresponding to the shape of the obstacle surface.

[0014] Furthermore, the verification method for whether the points in the point set can be fitted to the complete ground includes:

[0015] Linear fitting is performed based on the distance information of points in the point set using the least squares method;

[0016] Based on the distance information after the straight line fitting, determine the slope of the change of the distance information under the straight line fitting, and determine the intercept of the change based on the slope;

[0017] When the change in distance information between two adjacent points is the same as the change intercept, it is determined that the two adjacent points can be fitted to the ground.

[0018] When the change in distance information between two adjacent points is different from the change intercept, it is determined that the two adjacent points cannot be fitted to the ground.

[0019] Furthermore, when the points in the point set cannot be fitted to a complete ground surface, the method also includes:

[0020] For points where the change in distance information changes abruptly, extract the distance information of the two adjacent points on both sides;

[0021] When the distance information of the points on both sides of the point where the change in distance information changes abruptly is the same, the distance information of the point where the change in distance information changes abruptly is modified to be the same as the distance information of the adjacent points.

[0022] Furthermore, when the points in the point set cannot be fitted to a complete ground surface, the method also includes:

[0023] For points where the change in distance information changes abruptly, extract the distance information of the points corresponding to the points where the change in distance information changes abruptly from the point set of the previous frame return signal and the point set of the point set of the return signals of the subsequent preset number of frames.

[0024] When the change in the extracted distance information exceeds a preset value, delete points in the point set whose distance information changes abruptly.

[0025] Furthermore, after obtaining several clusters, the method also includes:

[0026] Determine whether the cluster size is abnormally small based on the number of nodes in the cluster;

[0027] If the number of points in a cluster is less than a preset number, the cluster is deleted.

[0028] Furthermore, after obtaining several clusters, the method also includes:

[0029] The variance of the x-axis coordinates of the midpoints in the cluster is used to determine whether the cluster is abnormally dispersed, where the x-axis is perpendicular to the direction of movement of the mobile robot;

[0030] When the variance of the x-axis coordinates of points in a cluster exceeds a preset isolation value, the cluster is deleted.

[0031] Furthermore, when the surface of the obstacle is a vertical obstacle, the height of the obstacle is determined based on the height difference between the highest point in the obstacle cluster with the highest point and the ground height. And based on the minimum distance information in the obstacle cluster and the corresponding return signal tilt angle, the distance between the obstacle and the mobile robot is calculated using trigonometric functions, wherein the difference between the height of the highest point and the ground height is calculated using coordinates in a coordinate system.

[0032] Furthermore, when the surface of the obstacle is considered to be a cylindrical obstacle, the coordinates of the center of the obstacle are determined by using the formula for finding the center of a circle from three points on a circle, based on the coordinates of the three points with the highest height in the obstacle cluster.

[0033] The radius of the obstacle is determined based on the coordinates of the center of the obstacle and the distance between any one of the three points.

[0034] The height of the obstacle is determined by the sum of the height of the obstacle's center and the obstacle's radius.

[0035] Based on the minimum distance information in the obstacle cluster and the corresponding tilt angle of the return signal, the distance between the obstacle and the mobile robot is calculated using trigonometric functions.

[0036] To address the aforementioned technical problems, this application also provides a wall-side distance measurement device based on side-line laser, employing the following technical solution:

[0037] The wall-mounted distance measurement device based on side-line laser includes the following steps:

[0038] The collection module is used to emit a line laser in front of the mobile robot and resolve the returned signal into a set of points with distance information; the line laser is perpendicular to the horizontal plane and points to the ground at a preset distance from the mobile robot;

[0039] A drawing module is used to draw the point set in a coordinate system based on distance information;

[0040] The fitting module is used to fit the distance information of the point set to obtain the intercept of the change in the distance information of adjacent points in the point set; and to determine whether the points in the point set can be fitted into a complete ground by verifying whether the rate of change of the distance information of adjacent points in the point set conforms to the intercept.

[0041] The clustering module is used to cluster points whose distance differences are within a preset range when the points in the point set cannot fit a complete ground; thus obtaining several clusters.

[0042] The labeling module is used to select the cluster with the smallest distance information from all clusters as the obstacle and find the center of the obstacle;

[0043] The ranging module is used to determine the actual distance between the obstacle and the mobile robot based on the distance information from the center of the obstacle to the mobile robot and the tilt angle between the plane where the line laser is located and the ground.

[0044] To address the aforementioned technical problems, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that: when the processor executes the computer program, it implements the steps of the wall distance measurement method based on side-line laser as described above.

[0045] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the steps of the wall-distance measurement method based on side-line laser as described above.

[0046] Compared with existing technologies, the embodiments of this application have the following main advantages: By emitting a line laser beam towards the ground in front of the mobile robot, the line laser beam is perpendicular to the horizontal plane, thus enabling the reception of reflected signals formed by a set of points. A prism is provided at the exit of the line laser beam to ensure the spacing of the emitted beams. Therefore, if the ground in front of the cleaning robot is flat, the light spot formed by the line laser beam is perpendicular to the direction of movement of the mobile robot. In this case, the distance information generated by the point set changes at equal intervals.

[0047] The coordinate system is established based on the plane containing the point set formed by the line laser, where the x-axis is the distance between the points in the point set and the laser transceiver in the horizontal direction, and the y-axis is the height of the points in the point set.

[0048] By fitting the distance information of the point set, it is determined whether the distance information of the point set conforms to the changing intercept, and thus whether the line laser is completely illuminating the flat ground.

[0049] If it cannot be determined through fitting that the line laser completely illuminates a flat surface, then the change in distance information from the point set generated by the line laser will definitely be uneven. In this case, clustering is used to group points with smooth distance changes, forming a cluster. Several clusters are formed in this way. Some clusters are point sets obtained from reflections of the line laser on the ground, while others are point sets obtained from reflections of the line laser on obstacles. Based on the changes in height and horizontal direction of points in the distance information clusters, it is determined whether the cluster belongs to an obstacle similar to a wall or is considered a cylindrical obstacle. Obstacles whose side opposite the laser transceiver does not present a vertical surface are considered cylindrical obstacles. The height of the obstacle is then calculated accordingly. This method uses a vertically placed laser transceiver to emit and receive reflected line lasers, determines the presence of obstacles through line fitting, and determines the type of obstacle and calculates the side-view obstacle distance through clustering. It involves fewer computations and less computation per operation. Attached Figure Description

[0050] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart of an embodiment of the wall distance measurement method based on side-line laser according to this application;

[0052] Figure 2 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0054] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0055] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0056] refer to Figure 1 The diagram shows a flowchart of an embodiment of the wall distance measurement method based on side-line laser according to this application.

[0057] The wall-side distance measurement method based on side-line laser includes the following steps:

[0058] Step S100: A vertical laser beam is emitted to the left or right side of the mobile robot, and the returned signal is parsed into a set of points with distance information; the plane in which the set of points formed by the laser beam is located is perpendicular to the horizontal plane, and;

[0059] By illuminating the ground in front of the mobile robot with a linear laser beam perpendicular to the horizontal plane, the reflected signal from a set of points can be received. A prism at the laser's exit point ensures the spacing of the emitted laser beams. Thus, if the ground in front of the cleaning robot is flat, the laser spot formed on the ground is perpendicular to the robot's direction of travel. The distance information generated by this set of points changes at equal intervals.

[0060] Step S200: Plot the point set in the coordinate system according to the distance information;

[0061] Distance information refers to the attribute values ​​generated by the emission and reception of the line laser itself. The line laser transceiver receives the reflected signal and acquires the distance information to determine the distance from the laser-illuminated point to the line laser transceiver, as well as the angle information of the reflected signal. However, distance and angle information can only be used to determine the distance and angle generated by an individual point, and are not suitable for analyzing the positional relationships between points in a set of points. The point set is plotted in a positioning coordinate system based on the distance information. The coordinate system is established based on the plane where the point set formed by the line laser is located, where the x-axis is the horizontal distance between the points in the point set and the laser transceiver, and the y-axis is the height of the points in the point set.

[0062] Step S300: Fit the distance information of the point set to obtain the change intercept of the distance information of adjacent points in the point set; and determine whether the points in the point set can be fitted into a complete ground by verifying whether the rate of change of the distance information of adjacent points in the point set conforms to the change intercept.

[0063] By fitting the distance information of the point set, it is determined whether the distance information of the point set conforms to the changing intercept, and thus whether the line laser is completely illuminating the flat ground.

[0064] Step S400: When the points in the point set cannot be fitted to a complete ground, based on the distance information of the points in the point set, the points whose distance information differences are within a preset range are clustered; to obtain several clusters, wherein the proportion of the difference between the height of the points in the cluster and the ground height being less than a distance threshold exceeds a proportion threshold, then the cluster is a ground cluster; the cluster in which the difference between the height of the points in the cluster and the ground height exceeds a preset value is an obstacle cluster;

[0065] If it cannot be determined through fitting that the line laser completely illuminates a flat surface, then the changes in distance information from the points generated by the line laser will certainly be uneven. In this case, clustering is used to group together points with smooth distance changes, forming a cluster. This process creates several clusters. Some clusters are point sets obtained from reflections of the line laser on the ground, while others are point sets obtained from reflections of the line laser on obstacles. Based on the changes in height and horizontal direction of the points in the distance information clusters, it is determined whether the cluster belongs to an obstacle similar to a wall or is considered a cylindrical obstacle.

[0066] Step S500: Determine whether the obstacle is a vertical surface using the wall determination method; wherein the wall determination method extracts the ground cluster and the obstacle cluster with the highest point height. When the points in the obstacle cluster can be fitted to a straight line, and the straight line is perpendicular to the straight line fitted by the points in the ground cluster in the coordinate system, it is determined that the obstacle is a vertical surface.

[0067] Step S600: Alternatively, determine whether an obstacle is considered to have a cylindrical surface by using a cylindrical judgment method; wherein the cylindrical judgment method extracts the obstacle cluster with the highest point height, and when there are adjacent points in the obstacle cluster with increasingly higher heights and increasingly greater horizontal distances from the mobile robot, the obstacle is determined to be an obstacle with a cylindrical surface.

[0068] Step S700: When the surface of the obstacle is a straight surface, or when the obstacle is regarded as an obstacle with a cylindrical surface, the height of the obstacle and the distance between it and the mobile robot are calculated by the detection method corresponding to the shape of the obstacle surface.

[0069] In this method, obstacles whose opposite side to the laser transceiver does not present a vertical surface are considered cylindrical obstacles, and their height is then calculated using a corresponding method. This method uses a vertically placed laser transceiver to emit a linear laser beam and receive the reflected beam. It determines the presence of obstacles through linear fitting and identifies the type of obstacle through clustering, calculating the distance to the obstacle from the side view. This method involves fewer computations and less computation per operation.

[0070] Furthermore, the verification method for whether the points in the point set can be fitted to the complete ground includes:

[0071] Linear fitting is performed based on the distance information of points in the point set using the least squares method;

[0072] Based on the distance information after the straight line fitting, determine the slope of the change of the distance information under the straight line fitting, and determine the intercept of the change based on the slope;

[0073] When the change in distance information between two adjacent points is the same as the change intercept, it is determined that the two adjacent points can be fitted to the ground.

[0074] When the change in distance information between two adjacent points is different from the change intercept, it is determined that the two adjacent points cannot be fitted to the ground.

[0075] Because when a line laser completely illuminates the ground, it forms a line segment, and by using the least squares method to fit a straight line, the intercept between adjacent points in the point set can be obtained more accurately.

[0076] Furthermore, when the points in the point set cannot be fitted to a complete ground surface, the method also includes:

[0077] For points where the change in distance information changes abruptly, extract the distance information of the two adjacent points on both sides;

[0078] When the distance information of the points on both sides of the point where the change in distance information changes abruptly is the same, the distance information of the point where the change in distance information changes abruptly is modified to be the same as the distance information of the adjacent points.

[0079] The line laser emitted by the laser transceiver may receive the returned signal only after multiple reflections, which will generate noise and affect the accuracy of the distance data. When the distance data of a point in the point set changes significantly, but the distance data of the two adjacent points before and after the above point are the same or the difference is less than a preset value, it means that the distance data of the above point is abnormal. At this time, the distance data of the abnormal point is modified according to the distance data of any adjacent point to eliminate the abnormality.

[0080] Furthermore, when the points in the point set cannot be fitted to a complete ground surface, the method also includes:

[0081] For points where the change in distance information changes abruptly, extract the distance information of the points corresponding to the points where the change in distance information changes abruptly from the point set of the previous frame return signal and the point set of the point set of the return signals of the subsequent preset number of frames.

[0082] When the change in the extracted distance information exceeds a preset value, delete points in the point set whose distance information changes abruptly.

[0083] When the distance data of points in a point set changes drastically, it may be due to interference caused by the reflection and refraction of light. Comparing this information with the distance information of corresponding points in the point set acquired in adjacent frames using a line laser is crucial. Even if the line laser detects an obstacle, the distance information of corresponding points in adjacent frames will not change drastically. If there is a significant change between two corresponding distance information sets, it indicates that the point where the abrupt change occurred has been interfered with, and the acquired data will be inaccurate.

[0084] Furthermore, after obtaining several clusters, the method also includes:

[0085] Determine whether the cluster size is abnormally small based on the number of nodes in the cluster;

[0086] If the number of points in a cluster is less than a preset number, the cluster is deleted.

[0087] The points in the point set are clustered, resulting in several clusters. Some clusters are of points irradiated on the ground, while others are of points irradiated on obstacles. However, the distance between adjacent points in the point set generated by line laser irradiation is very small. Therefore, the spatial range covered by several consecutive points is smaller than the width of a typical obstacle. Considering that the reflection and refraction of light may cover a certain area, causing errors in the detection of distance information of several consecutive points, if the number of points in a cluster is less than a preset value, the distance information of the points in that cluster is determined to be abnormal, and the corresponding cluster is deleted to prevent erroneous information from interfering with the judgment of obstacles.

[0088] Furthermore, after obtaining several clusters, the method also includes:

[0089] The variance of the x-axis coordinates of the midpoints in the cluster is used to determine whether the cluster is abnormally dispersed, where the x-axis is perpendicular to the direction of movement of the mobile robot;

[0090] When the variance of the x-axis coordinates of points in a cluster exceeds a preset isolation value, the cluster is deleted.

[0091] The variance of the x-axis coordinates of points in a cluster can reflect the fluctuation of the distance between each point in the cluster and the mobile robot. Obviously, obstacles usually have a face facing the mobile robot, and the distance change of the points generated by the line laser shining on this face must be gradual. Therefore, when the variance of the x-axis coordinates of the cluster points exceeds the set isolation value, the points in the cluster are severely disturbed. At this time, the cluster is deleted to improve the accuracy of obstacle recognition.

[0092] Furthermore, when the surface of the obstacle is a vertical obstacle, the height of the obstacle is determined based on the height difference between the highest point in the obstacle cluster with the highest point and the ground height. And based on the minimum distance information in the obstacle cluster and the corresponding return signal tilt angle, the distance between the obstacle and the mobile robot is calculated using trigonometric functions, wherein the difference between the height of the highest point and the ground height is calculated using coordinates in the coordinate system.

[0093] For wall-type obstacles that are perpendicular to the ground and whose points are evenly distributed in the cluster, the height of the obstacle can be determined by detecting the height of the highest point in the cluster in the coordinate system and calculating the height difference between the highest point and the ground in the coordinate system.

[0094] Furthermore, when the surface of the obstacle is considered to be a cylindrical obstacle, the coordinates of the center of the obstacle are determined by using the formula for finding the center of a circle from three points on a circle, based on the coordinates of the three points with the highest height in the obstacle cluster.

[0095] The radius of the obstacle is determined based on the coordinates of the center of the obstacle and the distance between any one of the three points.

[0096] The height of the obstacle is determined by the sum of the height of the obstacle's center and the obstacle's radius.

[0097] Based on the minimum distance information in the obstacle cluster and the corresponding tilt angle of the return signal, the distance between the obstacle and the mobile robot is calculated using trigonometric functions.

[0098] When the obstacle is not a wall, its shape is irregular. In this case, the obstacle is considered as a cylinder. By detecting this cylindrical obstacle, its approximate height and approximate distance from the mobile robot are determined. The error between the approximate height and distance and the actual value of the obstacle is negligible. The mobile robot crosses or avoids obstacles based on the approximate height and distance, unaffected by the error between the approximate height and distance and the actual value. Using the formula for finding the center of a circle from three points on the circle, the coordinates of the center of the cylinder's cross-section in the coordinate system can be detected. The distance between the center and any one of the three points on the circle is taken as the radius of the cylinder's cross-section. Therefore, the sum of the height of the cylinder's center and its radius is the height of the cylindrical obstacle.

[0099] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0100] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0101] To address the aforementioned technical problems, this application also provides a wall-side distance measurement device based on side-line laser, employing the following technical solution:

[0102] The wall-mounted distance measurement device based on side-line laser includes the following steps:

[0103] The collection module is used to emit a line laser in front of the mobile robot and resolve the returned signal into a set of points with distance information; the line laser is perpendicular to the horizontal plane and points to the ground at a preset distance from the mobile robot;

[0104] A drawing module is used to draw the point set in a coordinate system based on distance information;

[0105] The fitting module is used to fit the distance information of the point set to obtain the intercept of the change in the distance information of adjacent points in the point set; and to determine whether the points in the point set can be fitted into a complete ground by verifying whether the rate of change of the distance information of adjacent points in the point set conforms to the intercept.

[0106] The clustering module is used to cluster points whose distance differences are within a preset range when the points in the point set cannot fit a complete ground; thus obtaining several clusters.

[0107] The labeling module is used to select the cluster with the smallest distance information from all clusters as the obstacle and find the center of the obstacle;

[0108] The ranging module is used to determine the actual distance between the obstacle and the mobile robot based on the distance information from the center of the obstacle to the mobile robot and the tilt angle between the plane where the line laser is located and the ground.

[0109] Furthermore, the verification method for whether the points in the point set can be fitted to the complete ground includes:

[0110] The fitting submodule is used to perform line fitting based on the distance information of points in the point set using the least squares method.

[0111] The intercept calculation submodule is used to determine the slope of the change of the distance information under the straight line fitting based on the distance information after the straight line fitting, and to determine the changed intercept based on the slope.

[0112] The comparison submodule is used to determine that two adjacent points can be fitted to the ground when the change in distance information between two adjacent points is the same as the change intercept.

[0113] When the change in distance information between two adjacent points is different from the change intercept, it is determined that the two adjacent points cannot be fitted to the ground.

[0114] The method determines the existence of obstacles by fitting straight lines and determines the type of obstacles by clustering and calculates the distance to obstacles from the side view. The number of operations is small and the amount of computation per operation is small.

[0115] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 2 , Figure 2 This is a basic structural block diagram of the computer device in this embodiment.

[0116] The computer device 6 includes a memory 61, a processor 62, and a network interface 63 that are interconnected via a system bus. It should be noted that only the computer device 6 with components 61-63 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0117] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0118] The memory 61 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 61 may be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 may also be an external storage device of the computer device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 6. Of course, the memory 61 may also include both the internal storage unit and its external storage device of the computer device 6. In this embodiment, the memory 61 is typically used to store the operating system and various application software installed on the computer device 6, such as the program code of method X. In addition, the memory 61 can also be used to temporarily store various types of data that have been output or will be output.

[0119] In some embodiments, the processor 62 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 62 is typically used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is used to run program code stored in the memory 61 or process data, for example, to run the program code for the side-line laser-based wall distance measurement method.

[0120] The network interface 63 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 6 and other electronic devices.

[0121] This application also provides another embodiment, namely, a computer-readable storage medium storing a wall distance measurement program based on side-line laser, the wall distance measurement program based on side-line laser being executable by at least one processor to perform the steps of the wall distance measurement method based on side-line laser as described above.

[0122] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0123] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for measuring distance along a wall based on side-line laser, characterized in that, Includes the following steps: A vertical laser beam is emitted to the left or right of the mobile robot, and the returned signal is parsed into a set of points with distance information; the plane in which the set of points formed by the laser beam is located is perpendicular to the horizontal plane, and; The point set is plotted in the coordinate system based on the distance information; The distance information of the point set is fitted to obtain the intercept of the change in distance information between adjacent points in the point set; And by verifying whether the rate of change of the distance information between adjacent points in the point set conforms to the change intercept, it is determined whether the points in the point set can be fitted to a complete ground; When the points in the point set cannot be fitted to a complete ground, the points whose distance information is within a preset range are clustered according to the distance information of the points in the point set; several clusters are obtained, wherein the proportion of the points in the cluster whose height difference between the height and the ground height is less than a distance threshold exceeds a proportion threshold, then the cluster is a ground cluster; the cluster in which the height difference between the height and the ground height of the points exceeds a preset value is an obstacle cluster. Determine whether an obstacle is a vertical surface by using the wall judgment method; The wall identification method extracts the ground cluster and the obstacle cluster with the highest point height. When the points in the obstacle cluster can be fitted to a straight line, and the straight line is perpendicular to the straight line fitted to the points in the ground cluster in the coordinate system, the obstacle is determined to be an obstacle with a vertical surface. Alternatively, a cylindrical surface can be used to determine whether an obstacle is considered an obstacle. The cylindrical surface determination method extracts the obstacle cluster with the highest point. When there are adjacent points in the obstacle cluster with increasing height and increasing horizontal distance from the mobile robot, the obstacle is determined to be an obstacle with a cylindrical surface. When the surface of the obstacle is flat, or when the obstacle is considered to be a cylindrical surface, the height of the obstacle and the distance between it and the mobile robot are calculated by using the detection method corresponding to the shape of the obstacle surface. When the surface of the obstacle is a vertical obstacle, the height of the obstacle is determined based on the height difference between the highest point in the obstacle cluster with the highest point and the ground height. Furthermore, based on the minimum distance information in the obstacle cluster and the corresponding return signal tilt angle, the distance between the obstacle and the mobile robot is calculated using trigonometric functions. The difference between the height of the highest point and the ground height is calculated using coordinates in a coordinate system. When the surface of an obstacle is considered to be a cylinder, the coordinates of the center of the obstacle are determined by using the formula for finding the center of a circle from three points on a circle, based on the coordinates of the three points with the highest height in the obstacle cluster. The radius of the obstacle is determined based on the coordinates of the center of the obstacle and the distance between any one of the three points. The height of the obstacle is determined by the sum of the height of the obstacle's center and the obstacle's radius. Based on the minimum distance information in the obstacle cluster and the corresponding tilt angle of the return signal, the distance between the obstacle and the mobile robot is calculated using trigonometric functions.

2. The wall-side distance measurement method based on side-line laser as described in claim 1, characterized in that, The verification methods for whether the points in a point set can be fitted to a complete ground plane specifically include: Linear fitting is performed based on the distance information of points in the point set using the least squares method; Based on the distance information after the straight line fitting, determine the slope of the change of the distance information under the straight line fitting, and determine the intercept of the change based on the slope; When the change in distance information between two adjacent points is the same as the change intercept, it is determined that the two adjacent points can be fitted to the ground. When the change in distance information between two adjacent points is different from the change intercept, it is determined that the two adjacent points cannot be fitted to the ground.

3. The wall-side distance measurement method based on side-line laser as described in claim 1, characterized in that, When the points in the point set cannot be fitted to a complete ground, the method further includes: For points where the change in distance information changes abruptly, extract the distance information of the two adjacent points on both sides; When the distance information of the points on both sides of the point where the change in distance information changes abruptly is the same, the distance information of the point where the change in distance information changes abruptly is modified to be the same as the distance information of the adjacent points.

4. The wall-side distance measurement method based on side-line laser as described in claim 1, characterized in that, When the points in the point set cannot be fitted to a complete ground, the method further includes: For points where the change in distance information changes abruptly, extract the distance information of the points corresponding to the points where the change in distance information changes abruptly from the point set of the previous frame return signal and the point set of the point set of the return signal of the subsequent preset number of frames. When the change in the extracted distance information exceeds a preset value, delete points in the point set whose distance information changes abruptly.

5. The wall-side distance measurement method based on side-line laser as described in claim 1, characterized in that, After obtaining several clusters, the method further includes: Determine whether the cluster size is abnormally small based on the number of nodes in the cluster; If the number of points in a cluster is less than a preset number, the cluster is deleted.

6. The wall-side distance measurement method based on side-line laser as described in claim 1, characterized in that, After obtaining several clusters, the method further includes: The variance of the x-axis coordinates of the midpoints in the cluster is used to determine whether the cluster is abnormally dispersed, where the x-axis is perpendicular to the direction of movement of the mobile robot; When the variance of the x-axis coordinates of points in a cluster exceeds a preset isolation value, the cluster is deleted.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the wall distance measurement method based on side-line laser as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the wall-side distance measurement method based on side-line laser as described in any one of claims 1 to 6.

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