A laser radar distortion point cloud angle identification method and device and a robot

Abstract

The application relates to a laser radar distortion point cloud angle identification method and device and a robot, comprising the following steps: setting a calibration target according to position information of a support column, the support column being arranged at the periphery of a laser radar; acquiring a calibration point cloud generated by the laser radar at the calibration target; and determining an angle range of a distortion point cloud caused by the support column in the calibration point cloud. According to the method, the angle of the distortion point cloud caused by the support column is identified, the point cloud in the angle range is deleted or distance correction processing is performed on the point cloud, and the quality of the point cloud data is improved and the ranging accuracy of the point cloud is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to laser radar ranging positioning technology, and in particular to a laser radar distortion point cloud angle identification method and device and a robot. BACKGROUND

[0002] At present, with the improvement of sweeping robot technology and the increase of functions, the sweeping robot gradually replaces manual cleaning. The sweeping robot can accurately judge obstacles thanks to ultrasonic bionic detection technology and laser radar positioning technology. In order to protect the laser radar, prevent external objects from pressing, blocking rotation and scratching, and affect the normal function, the laser radar is generally embedded in the main body of the sweeping robot or externally placed on the upper part of the robot body after being equipped with a protective cover.

[0003] When the laser radar works normally, the light spot emitted by the laser radar is partially blocked or cut by the support column of the shell cover or the support column of the protective cover, and a distortion point cloud is generated near the support column. Therefore, distance deviation is caused after the light spot is extracted. If the light spot emitted by the laser radar is completely blocked by the support column, point cloud loss will be caused, and a gap will appear at the support column. Due to the existence of the gap and the distortion point cloud, deviation occurs when the sweeping robot measures the distance, which affects the normal driving of the sweeping robot. SUMMARY

[0004] The technical problem solved by the embodiments of the present application is to provide a laser radar distortion point cloud angle identification method, device and robot. The distortion point cloud is identified by angle, the distortion point cloud in the angle range is processed, and the quality of the point cloud data and the ranging accuracy are improved.

[0005] In a first aspect, a laser radar distortion point cloud angle identification method is provided in the embodiments of the present application, and the method comprises:

[0006] Setting a calibration target according to position information of a support column, the support column being arranged around the laser radar;

[0007] Obtaining a calibration point cloud generated by the laser radar at the calibration target;

[0008] Determining an angle range of a distortion point cloud caused by the support column in the calibration point cloud.

[0009] In some embodiments, the setting of the calibration target according to the position information of the support column comprises:

[0010] Obtaining a range range of the laser radar and position information of a support column around the laser radar;

[0011] Setting a placement range and a placement position of the calibration target according to the range range and the position information of the support column;

[0012] placing a calibration target according to the placement range and the placement position.

[0013] In some embodiments, the determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column comprises:

[0014] determining whether there is a continuous point cloud in the calibration point cloud, if yes, taking an average value of angles of the continuous point cloud as a reference angle corresponding to the support column, and determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the reference angle; or

[0015] determining whether there is a continuous point cloud in the calibration point cloud, if no, and the support column position does not generate a point cloud, calculating an absolute value of a distance difference between every two adjacent points in the calibration point cloud, taking an average value of angles of the two adjacent points with the absolute value of the distance difference greater than a preset threshold as the reference angle corresponding to the support column, and determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the reference angle; or

[0016] if the support column position generates a point cloud, eliminating the point cloud corresponding to the support column position in the calibration point cloud to obtain a corrected calibration point cloud, calculating an absolute value of a distance difference between every two adjacent points in the corrected calibration point cloud, taking an average value of angles of the two adjacent points with the absolute value of the distance difference greater than a preset threshold as the reference angle corresponding to the support column, and determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the reference angle.

[0017] In some embodiments, the determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column comprises:

[0018] obtaining a measured distance of each point in the calibration point cloud;

[0019] determining an actual distance of each point in the calibration point cloud from the lidar;

[0020] calculating an absolute value of a distance difference between the measured distance and the actual distance of each point in the calibration point cloud;

[0021] obtaining an angle value of a continuous point cloud with the absolute value of the distance difference greater than a distance threshold, and determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the angle value.

[0022] In some embodiments, the calibration target is a circular ring target, and the determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column comprises:

[0023] obtaining a measured brightness of each point in the calibration point cloud;

[0024] determine a standard brightness of the calibration point cloud based on the measured brightness;

[0025] calculate an absolute value of a brightness difference between the measured brightness and the standard brightness of each point in the calibration point cloud;

[0026] obtain an angle value of a continuous point cloud with an absolute value of a brightness difference greater than a brightness threshold, and determine an angle range of a distorted point cloud caused by the support column in the calibration point cloud based on the angle value.

[0027] In some embodiments, the determining the angle range of the distorted point cloud caused by the support column in the calibration point cloud based on the reference angle comprises:

[0028] extending the reference angle to the left by a first preset angle to obtain a first angle region;

[0029] extending the reference angle to the right by a second preset angle to obtain a second angle region;

[0030] obtaining the angle range of the distorted point cloud caused by the support column in the calibration point cloud based on the first angle region and the second angle region.

[0031] In some embodiments, after the determining the angle range of the distorted point cloud caused by the support column in the calibration point cloud, the method further comprises:

[0032] obtaining point cloud data generated by the laser radar in an actual ranging process, deleting or performing distance correction processing on the point cloud in the angle range of the distorted point cloud to obtain processed point cloud data.

[0033] In some embodiments, the calibration target is a closed or non-closed polygon or a circular ring.

[0034] In a second aspect, an embodiment of the present application provides a laser radar distorted point cloud angle identification device, comprising:

[0035] a setting module configured to set a calibration target according to position information of a support column, the support column being arranged around the laser radar;

[0036] an obtaining module configured to obtain a calibration point cloud generated by the laser radar at the calibration target;

[0037] a determining module configured to determine an angle range of a distorted point cloud caused by the support column in the calibration point cloud.

[0038] In a third aspect, an embodiment of the present application provides a laser radar, comprising:

[0039] at least one processor, and

[0040] a memory communicatively connected with the at least one processor, wherein,

[0041] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.

[0042] In a fourth aspect, the embodiments of the present application provide a robot, comprising the laser radar in the third aspect.

[0043] The embodiments of the present application have the beneficial effects that: different from the related art, the laser radar distortion point cloud angle identification method provided by the embodiments of the present application sets a calibration target according to position information of a support column, the support column is arranged around the laser radar, a calibration point cloud generated by the laser radar at the calibration target is acquired, and an angle range of a distortion point cloud caused by the support column in the calibration point cloud is determined. The method identifies the angle of the distortion point cloud caused by the support column, deletes or performs distance correction processing on the point cloud in the angle range, and improves the quality of the point cloud data and the ranging accuracy of the point cloud. BRIEF DESCRIPTION OF DRAWINGS

[0044] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, which are schematic and not intended to be limiting of the embodiments, and in which like reference numerals designate similar elements in the figures and wherein the use of "for example", "e.g.", "of the embodiments", "an embodiment", "one embodiment", "some embodiments", "exemplary embodiment", "one

[0045] Figure 1 is an application environment schematic diagram of a laser radar distortion point cloud angle identification method provided by the embodiments of the present application;

[0046] Figure 2 is a flow schematic diagram of a laser radar distortion point cloud angle identification method provided by the embodiments of the present application;

[0047] Figure 3 is a structure schematic diagram of calibration of some different shape calibration targets provided by the embodiments of the present application;

[0048] Figure 4 is a partial schematic diagram of formation of calibration point clouds on some calibration targets provided by the embodiments of the present application;

[0049] Figure 5 is a schematic diagram of formation of calibration point clouds by a straight plate calibration target provided by the embodiments of the present application;

[0050] Figure 6 is a schematic diagram of formation of calibration point clouds by a circular ring calibration target provided by the embodiments of the present application;

[0051] Figure 7is a schematic diagram of forming a calibration point cloud by a circular ring calibration target provided by an embodiment of the present application;

[0052] Figure 8 is a structural schematic diagram of a laser radar distortion point cloud angle recognition device provided by an embodiment of the present application;

[0053] Figure 9 is a structural schematic diagram of a laser radar provided by an embodiment of the present application;

[0054] Figure 10 is a structural schematic diagram of a robot provided by an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0056] It should be noted that, if there is no conflict, each feature in the embodiments of the present application can be combined with each other, and all within the protection scope of the present application. In addition, although the functional modules are divided in the device schematic diagram, and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in different order from the module division in the device or the order in the flowchart. In addition, the "first", "second", "third" and the like used herein do not limit the data and execution order, but only distinguish the same items or similar items with basically the same function and effect.

[0057] Unless otherwise defined, all technical and scientific terms used in the specification are the same as those commonly understood by those skilled in the art to which the present application belongs. The terms used in the specification of the present application are only for the purpose of describing the specific embodiments and are not used to limit the present application. The term "and / or" used in the specification includes any and all combinations of one or more related listed items.

[0058] In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as there is no conflict.

[0059] Please refer to Figure 1 , Figure 1 The application environment schematic diagram of the laser radar distortion point cloud angle recognition method provided by an embodiment of the present application is shown as Figure 1 , which includes a robot 10 and sofa, tea table, potted plants and other target objects.

[0060] The robot 10 is provided with a laser radar 11, which scans a target object to obtain point cloud data, and calculates the distance between the target object and the laser radar based on the point cloud data.

[0061] The laser radar comprises a transmitter, a receiver, a processor and a rotating mechanism. The transmitter is a device for emitting laser light; the receiver is a device for receiving laser light; the processor is mainly responsible for controlling the transmitter to emit laser light and processing the laser signals received by the receiver to calculate the distance information of the target object; and the rotating mechanism is a laser radar mounting skeleton for adjusting the direction. The transmitter, the receiver and the processor are arranged on the rotating mechanism, and the rotating mechanism rotates at a stable speed, so that the laser radar can scan the surrounding environment and generate real-time point cloud information.

[0062] The point cloud data produced by the laser radar includes the angle, distance and brightness of each point. The angle is the angle of the light spot formed by the laser hitting the target object in the polar coordinate, the distance is the distance from the light spot formed by the laser hitting the target object to the laser radar, and the brightness is the brightness of the light spot.

[0063] When the target object is close to the laser radar, due to the limited width of the receiver, the light spot of the reflected laser light cannot fall within the field of view of the receiver or only part of the light spot falls within the field of view of the receiver, so there is a blind area.

[0064] The laser radar is usually provided with support columns around it. When the laser radar is rotating, the transmitter will be blocked by a support column at a certain angle once, and the receiver will also be blocked by the support column once as the laser radar rotates. When the laser radar is working normally, whether the transmitter is completely blocked or the receiver is completely blocked, it will cause the point cloud at the angle of the support column to be invalid, i.e. the point cloud is missing, resulting in a gap at the support column. The light spot of the laser radar is divided or partially blocked by the support column, which will produce distorted point cloud within a certain range at the angle, resulting in a distance deviation when the center of the light spot is extracted for distance measurement.

[0065] It should be noted that, in general, a single support column at the same angle or tangent direction within the near distance blind area of the laser radar will produce two gaps, a single support column at the same angle or tangent direction outside the blind area will produce one or two gaps, and two support columns at the same angle or tangent direction outside the blind area will produce two or three gaps.

[0066] In the process of normal use of the robot, due to the influence of the distorted point cloud and the gap, the ranging of the laser radar is inaccurate. In view of the above problems, the application embodiment provides a laser radar distorted point cloud angle identification method. The point cloud in the angle range is deleted or distance correction processing is performed thereon. The accurate distance is calculated based on the processed point cloud data, and is used to guide the movement and obstacle avoidance of the robot.

[0067] Specifically, refer to Figure 2 , Figure 2 is a flowchart of a laser radar distorted point cloud angle identification method provided by the application embodiment. The method specifically includes the following steps:

[0068] Step S1: setting a calibration target according to the position information of the support column, the support column being arranged around the laser radar;

[0069] Step S2: acquiring calibration point cloud generated by the laser radar at the calibration target;

[0070] Step S3: determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column.

[0071] Generally, the laser radar is embedded under the machine shell cover or externally arranged on the machine shell cover. When the laser radar is embedded under the machine shell cover, in order to effectively support the machine shell cover, a support column needs to be arranged around the laser radar. The single support column is linearly connected to the center of the laser radar or tangent to the outer surface of the laser radar. A plurality of support columns can be arranged, and the plurality of support columns are linearly connected to the center of the laser radar or tangent to the outer surface of the laser radar. When the laser radar is externally arranged on the machine shell cover, the laser radar is provided with a protective cover, and a plurality of support columns are also arranged on the protective cover.

[0072] In order to obtain the point cloud information of the laser radar, a calibration target needs to be set according to the position of the support column. The calibration target includes a homogeneous calibration target and a non-homogeneous calibration target. The homogeneous calibration target refers to a calibration target made of the same material, such as a homogeneous white paperboard or plastic plate. The non-homogeneous calibration target uses materials with different absorption and scattering abilities of laser, which will affect the brightness of the light spot in the use process. Therefore, in the application embodiment, the calibration target only needs to be homogeneous.

[0073] The calibration point cloud is obtained by placing a calibration target around the laser radar to calibrate the laser radar. The point cloud in the calibration point cloud is arranged in order from small to large according to the generation time. In the calibration point cloud, the coordinates, distance, angle and brightness of each point can be obtained. The distance is the distance from the light spot formed by the laser on the calibration target to the laser radar, the angle is the angle of the light spot formed by the laser on the calibration target in the polar coordinate, the coordinates are the position coordinates of the light spot formed by the laser on the calibration target in the rectangular coordinate system, and the brightness is the brightness of the light spot.

[0074] Specifically, a calibration target of the same material is arranged in front of the laser radar, a straight line where the shortest distance from the center of the laser radar to the calibration target is located is perpendicular to the calibration target, and the placement distance between the calibration target and the laser radar is determined according to the range of the laser radar. When the laser radar performs laser scanning ranging on the calibration target, the processor thereof calculates the coordinates, distance, angle and brightness of each light spot formed on the calibration target based on the emitted laser information and the echo laser information. The calculation of the coordinates, distance, angle and brightness of the light spot is the existing calculation method of the laser radar.

[0075] When the laser radar works normally, the transmitter and the receiver are blocked by a support column at a certain angle as the laser radar rotates. Whether the transmitter or the receiver is blocked, it will cause the point cloud at the angle of the support column to be missing, resulting in a gap at the support column. Because the light spot of the laser radar is divided or partially blocked by the support column, distorted point cloud will be generated within a certain range at the angle, which will cause distance deviation when the light spot center is extracted for ranging. By determining the angle range of the distorted point cloud, the point cloud at the angle is corrected or deleted to improve the ranging accuracy of the point cloud.

[0076] In some embodiments, the calibration target is arranged according to the position information of the support column, including: acquiring the range of the laser radar and the position information of the support column around the laser radar; arranging the placement range and the placement position of the calibration target according to the range and the position information of the support column; and placing the calibration target according to the placement range and the placement position.

[0077] The range of the laser radar refers to the nearest distance to the farthest distance of the target object that can be hit by the laser radar.

[0078] If there are multiple support columns in different directions around the laser radar, calibration targets need to be arranged directly in front of each support column.

[0079] The distance range of the placement position of the calibration target and the laser radar is determined according to the range of the laser radar. For example, the range of a certain laser radar is [D min , D max ], unit: mm, the minimum value of the distance (the distance perpendicular to the calibration target) at which the calibration target can be placed is d1, then:

[0080] d1=α*D min +bias1

[0081] wherein α is a scaling factor, bias1 is a bias factor, and D min is the minimum distance value of the ranging of the laser radar.

[0082] It can be understood that the specific values of a and bias1 are values set by those skilled in the art according to specific circumstances.

[0083] The maximum value of the distance (the distance of the laser beam perpendicular to the calibration target) at which the calibration target can be placed is d2, and then:

[0084] d2 = β * D max + bias2

[0085] wherein β is a scaling coefficient, bias2 is a bias coefficient, D max is the maximum distance value of the laser radar ranging.

[0086] It can be understood that the specific values of β and bias2 are values set by those skilled in the art according to specific circumstances.

[0087] Therefore, the distance (the distance of the laser beam perpendicular to the calibration target) at which the calibration target can be placed is [d1, d2].

[0088] In some embodiments, as Figure 3 shown, Figure 3 are structural schematic diagrams of calibration of some different shapes of calibration targets provided by the embodiments of the present application. Figure 3 (a) The shape of the calibration target is a triangle, wherein there are three support columns 12 around the laser radar 13, and each of the support columns 12 has a calibration target 11 in front of it. The shortest laser beam emitted by the laser radar 13 is perpendicular to the triangular calibration target 11. It should be noted that the optimal position of the calibration target is that the straight line connecting the laser radar 13 and the support column 12 is perpendicular to the calibration target. Figure 3 (b) The shape of the calibration target is a quadrilateral, and there are four support columns 22 around the laser radar 23, and each of the support columns 22 has a calibration target 21 in front of it. The shortest laser beam emitted by the laser radar 23 is perpendicular to the quadrilateral calibration target 21. Figure 3 (c) The shape of the calibration target is a circular ring, and the laser radar 33 is located at the center of the circular ring calibration target 31. Since the shape of the calibration target 31 is a circular ring, the support columns around the laser radar 33 can display the point cloud data on the circular ring calibration target in order and equidistantly, without considering the number of support columns and the length of the calibration target.

[0089] wherein the calibration target can be a closed or non-closed polygon or a circular ring. If the calibration target is non-closed, each separate calibration target needs to correspond to each support, so that the gap point cloud formed by the support column can be displayed on the calibration target. For example, if there is only a single support column around the laser radar, only a straight plate calibration target corresponding to the support column is needed to satisfy that the gap point cloud formed by the support column can be displayed on the calibration target.

[0090] It can be understood that the circular calibration target does not need to consider the number of support columns and the length of the calibration target when in use, and the circular calibration target occupies small space, is easy to build, and has strong practicability. When point cloud calibration is performed, the circular calibration target can be considered as a preferred calibration device.

[0091] In some embodiments, the determining of the angle range of the distorted point cloud in the calibration point cloud caused by the support column comprises:

[0092] If yes, the average angle of the continuous point cloud is taken as the reference angle corresponding to the support column, and the angle range of the distorted point cloud in the calibration point cloud caused by the support column is determined based on the reference angle; or

[0093] If no, and the support column position does not generate point cloud, the absolute value of the distance difference of each adjacent two points in the calibration point cloud is calculated, the average angle of the adjacent two points with the absolute value of the distance difference greater than a preset threshold is taken as the reference angle corresponding to the support column, and the angle range of the distorted point cloud in the calibration point cloud caused by the support column is determined based on the reference angle; or

[0094] If the support column position generates point cloud, the point cloud corresponding to the support column position in the calibration point cloud is removed to obtain a corrected calibration point cloud, the absolute value of the distance difference of each adjacent two points in the corrected calibration point cloud is calculated, the average angle of the adjacent two points with the absolute value of the distance difference greater than a preset threshold is taken as the reference angle corresponding to the support column, and the angle range of the distorted point cloud in the calibration point cloud caused by the support column is determined based on the reference angle.

[0095] When the receiver cannot capture the light spot of the laser, the software algorithm in the lidar sets the valid bit of the point cloud data at the angles in this case to 0, and the distance and brightness of the data point cloud with the valid bit of 0 are both 0 (the angle value is normal). The preset value is 0.

[0096] Please refer to Figure 4 , Figure 4 are partial schematic diagrams of forming calibration point clouds on some calibration targets provided by the embodiments of the present application, Figure 4 (a) is a calibration point cloud formed on a polygonal calibration target, which comprises a lidar 43, a support column 42, a normal point cloud 44 and a distorted point cloud 41. Figure 4 (b) is a calibration point cloud formed on a circular calibration target, which comprises a lidar 53, a support column 52, a normal point cloud 51 and a distorted point cloud 54.

[0097] By Figure 4The calibrated point cloud shown in the figure can be known that if the support column is in the blind area and the width of the support column can completely block the light spot, the effective bit of the point cloud at this angle is 0, and the average value of the angles of these point clouds is taken as the reference angle corresponding to the support column. If the support column is in the blind area, but the width of the support column cannot completely block the light spot, the absolute value of the distance difference of each adjacent two points in the calibrated point cloud is calculated, and the average value of the angles of the two points whose absolute value of the distance difference is greater than the preset threshold is taken as the reference angle corresponding to the support column. If the support column is outside the blind area, the width of the support column cannot completely block the light spot, the absolute value of the distance difference of each adjacent two points in the calibrated point cloud is calculated, and the average value of the angles of the two points whose absolute value of the distance difference is greater than the preset threshold is taken as the reference angle corresponding to the support column. If the support column is outside the blind area, the width of the support column can completely block the light spot, the point cloud at the support column is removed to obtain the corrected calibrated point cloud, the absolute value of the distance difference of each adjacent two points in the corrected calibrated point cloud is calculated, and the average value of the angles of the two points whose absolute value of the distance difference is greater than the preset threshold is taken as the reference angle corresponding to the support column.

[0098] It should be noted that the distance between the support column and the laser radar is known when the robot is shipped, and the distance can be directly used when the point cloud at the support column is removed. The preset distance is set according to the gap in the calibrated point cloud, for example, if there is only one gap in the calibrated point cloud, the preset threshold can be set according to the maximum value of the absolute value of the distance difference of each adjacent two points in the calibrated point cloud, and if there are two gaps in the calibrated point cloud, the preset threshold can be set according to the second maximum value of the absolute value of the distance difference of each adjacent two points in the calibrated point cloud.

[0099] In some embodiments, the determining the angle range of the distorted point cloud in the calibrated point cloud caused by the support column comprises:

[0100] Obtaining the measured distance of each point in the calibrated point cloud;

[0101] Determining the actual distance of each point in the calibrated point cloud from the laser radar;

[0102] Calculating the absolute value of the distance difference of the measured distance and the actual distance of each point in the calibrated point cloud;

[0103] Obtaining the angle value of the continuous point cloud whose absolute value of the distance difference is greater than the distance threshold, and determining the angle range of the distorted point cloud in the calibrated point cloud caused by the support column based on the angle value.

[0104] Please refer to Figure 5 , Figure 5is a schematic diagram of a straight plate calibration target forming a calibration point cloud provided by an embodiment of the present application. Wherein, the M point cloud vertical laser beam is the nearest point cloud to the laser radar 61, the distance of the M point is D, the angle is Angle, find out any normal point cloud Q on the straight plate calibration target, the distance of Q is d_i, the angle is angle_i, the angle of point Q relative to the M point is a, then:

[0105] D=d_i*cos a

[0106] If there is a distortion point cloud P, the measured distance of P is d_j, the angle is angle_j, and the actual distance value D_j of the distortion point, then:

[0107] D_j=D / cos(|angle_j-Angle|)

[0108] The difference between the measured distance and the actual distance of the distortion point cloud is d1, then:

[0109] d1=|d_j-D_j|

[0110] If d1 is greater than the distance threshold Thr1, the point cloud is a distortion point cloud.

[0111] Because the calibration target is placed at different distances, the distance deviation of the distortion point cloud near the gap is also different after being blocked by the supporting column. In order to accurately obtain the distortion point cloud, it is necessary to adaptively adjust the preset distance Thr1:

[0112] Thr1=a1*D 2 +b1*D+c1

[0113] Wherein, a1, b1, c1 are coefficient factors, and the specific values of a1, b1, c1 are values set by those skilled in the art according to specific conditions.

[0114] According to the method, the angle value of the continuous point cloud whose d1 is greater than the distance threshold Thr1 is obtained, and based on the angle value, the angle range of the distortion point cloud caused by the supporting column in the calibration point cloud can be determined.

[0115] Please refer to Figure 6 , Figure 6 is a schematic diagram of a circular ring calibration target forming a calibration point cloud provided by an embodiment of the present application. Wherein, the distance from the laser radar 71 to the calibration target is equal, for any point cloud H, there is an actual distance R, for the distortion point cloud S, the measured distance of the point is d_l, and the difference between the measured distance and the actual distance of the distortion point cloud is d2, then:

[0116] d2=|d_l-R|

[0117] If d2 is greater than the distance threshold Thh2, the point cloud is a distortion point cloud.

[0118] Since the distance between the calibration target and the support column is different, the distance deviation of the distorted point cloud near the gap is also different after being blocked by the support column. In order to accurately obtain the distorted point cloud, the preset distance Thr2 needs to be adaptively adjusted:

[0119] Thr2=a2*R+b2*R+c2 2

[0120] Wherein, a2, b2, c2 are coefficient factors, and the specific values of a2, b2, and c2 are values set by those skilled in the art according to specific conditions.

[0121] According to the method, the angle value of the continuous point cloud with Δd2 greater than the distance threshold Thr2 is obtained, and based on the angle value, the angle range of the distorted point cloud in the calibration point cloud caused by the support column can be determined.

[0122] In some embodiments, the calibration target is a circular ring target, and the determination of the angle range of the distorted point cloud in the calibration point cloud caused by the support column comprises:

[0123] Obtaining the measured brightness of each point in the calibration point cloud;

[0124] Determining the standard brightness of the calibration point cloud based on the measured brightness;

[0125] Calculating the absolute value of the brightness difference between the measured brightness and the standard brightness of each point in the calibration point cloud;

[0126] Obtaining the angle value of the continuous point cloud with the absolute value of the brightness difference greater than the brightness threshold, and determining the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the angle value.

[0127] Obtaining the measured brightness L_i of each point cloud in the calibration point cloud, taking the brightness with the highest occurrence frequency in the measured brightness as the standard brightness L_j, and calculating the difference Δl between the measured brightness and the standard brightness for each point cloud.

[0128] Δl=|L_i-L_j|

[0129] If Δl is greater than the brightness threshold Lhr, the point cloud is a distorted point cloud.

[0130] According to the method, the angle value of the continuous point cloud with Δl greater than the brightness threshold Lhr is obtained, and based on the angle value, the angle range of the distorted point cloud in the calibration point cloud caused by the support column can be determined.

[0131] In some embodiments, the determination of the angle range of the distorted point cloud in the calibration point cloud caused by the support column based on the reference angle comprises:

[0132] ​The reference angle is extended to the left by a first preset angle to obtain a first angle region;

[0133] The reference angle is extended to the right by a second preset angle to obtain a second angle region;

[0134] Based on the first angle region and the second angle region, an angle range of the distorted point cloud in the calibration point cloud caused by the support column is obtained.

[0135] It should be noted that the angle range determination method of the distorted point cloud in the calibration point cloud can be used for calibration of a polygonal calibration target or a circular ring calibration target. The first preset angle and the second preset angle are preset by a person skilled in the art, and the setting values of the first preset angle and the second preset angle of the same batch of laser radars are the same.

[0136] Please refer to Figure 7 , Figure 7 is another schematic diagram of a circular ring calibration target forming a calibration point cloud provided by the embodiment of the present application, wherein the laser radar 81 rotates clockwise, the average value of the angle values of the a1 point cloud and the a2 point cloud is taken as the angle value p1_angle of the left reference angle, and the average value of the angle values of the a3 point cloud and the a4 point cloud is taken as the angle value p2_angle of the right reference angle.

[0137] Taking the left reference angle p1_angle as a reference, the first preset angle Δθ1 is extended to the left to obtain a first angle region θ1, and the second preset angle Δθ2 is extended to the right to obtain a second angle region θ2, then:

[0138] θ1=p1_angle-Δθ1

[0139] θ2=p1_angle+Δθ2

[0140] Similarly, taking the right reference angle p2_angle as a reference, the third preset angle Δθ3 is extended to the left to obtain a third angle region θ3, and the fourth preset angle Δθ4 is extended to the right to obtain a fourth angle region θ4, then:

[0141] θ3=p2_angle-Δθ3

[0142] θ4=p2_angle+Δθ4

[0143] Therefore, the angle range of the distorted point cloud in the calibration point cloud is [θ1, θ2] and [θ3, θ4].

[0144] In some embodiments, after the angle range of the distorted point cloud in the calibration point cloud caused by the support column is determined, the method further comprises:

[0145] The point cloud data generated by the laser radar in the actual ranging process is acquired, and the point cloud in the angle range of the distorted point cloud in the point cloud data is deleted or distance correction processing is performed thereon to obtain processed point cloud data.

[0146] In summary, the laser radar distorted point cloud angle identification method provided in the embodiments of the present application sets a calibration target according to the position information of the support column, the support column is arranged around the laser radar, calibration point cloud generated by the laser radar at the calibration target is acquired, and the angle range of the distorted point cloud caused by the support column in the calibration point cloud is determined. In the identification of the angle range of the distorted point cloud, the angle range of the continuous distorted point cloud can be accurately determined by taking the distance threshold and the brightness threshold as the judgment standard, the error range is small, and the angle of the distorted point cloud is identified by the distance threshold, which is not limited by the shape of the calibration target and has a wide range of use. The angle of the distorted point cloud is identified by the angle threshold, which is not as accurate as the identification by the distance threshold and the brightness threshold, but the angle is identified by the angle threshold, which is easy to operate, has a small amount of calculation, and is not limited by the shape of the calibration target. The point cloud in the angle range of the distorted point cloud in the point cloud data is deleted or distance correction processing is performed thereon, which improves the quality of the point cloud data and improves the accuracy of the point cloud ranging.

[0147] Please refer to Figure 8 , Figure 8 is a structure schematic diagram of a laser radar distorted point cloud angle identification device provided in the embodiments of the present application. The device 100 comprises a setting module 101, an acquisition module 102, and a determination module 103.

[0148] The setting module 101 is configured to set a calibration target according to the position information of a support column, and the support column is arranged around the laser radar. The acquisition module 102 is configured to acquire calibration point cloud generated by the laser radar at the calibration target. The determination module 103 is configured to determine the angle range of the distorted point cloud caused by the support column in the calibration point cloud.

[0149] In the embodiments of the present application, the laser radar distorted point cloud angle identification device can also be built by hardware devices, for example, the laser radar distorted point cloud angle identification device can be built by one or more than two chips, and each chip can work in coordination with each other to complete the laser radar distorted point cloud angle identification method described in the above embodiments. For another example, the laser radar distorted point cloud angle identification device can also be built by various logic devices, such as general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), single-chip microcomputers, ARM (Acorn RISC Machine), or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, or any combination of these components.

[0150] The laser radar distortion point cloud angle recognition device in the embodiment of the application can be a device with an operating system. The operating system can be an Android operating system, an ios operating system, or other possible operating systems, and the embodiment of the application does not make specific limitations.

[0151] It should be noted that the laser radar distortion point cloud angle recognition device described above can execute the laser radar distortion point cloud angle recognition method provided in the embodiment of the application, and has the corresponding function modules and beneficial effects of executing the method. Technical details not described in detail in the embodiment of the laser radar distortion point cloud angle recognition device can be referred to the laser radar distortion point cloud angle recognition method provided in the embodiment of the application.

[0152] The application also provides a laser radar. Please refer to Figure 9 , Figure 9 is a structural schematic diagram of a laser radar provided in the embodiment of the application. The laser radar 200 includes at least one processor 201 and a memory 202 connected with the at least one processor 201 in communication, wherein the memory 202 stores instructions executable by the at least one processor 201, and the instructions are executed by the at least one processor 201 to enable the at least one processor 201 to execute the laser radar distortion point cloud angle recognition method in any method embodiment described above. The processor 201 and the memory 202 can be connected by a bus or other means, Figure 9 for example, by a bus connection in the embodiment.

[0153] The processor 201 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof; and can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The above-mentioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0154] The memory 202, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the laser radar distorted point cloud angle identification method in the embodiments of the present application. The processor 201 can implement the laser radar distorted point cloud angle identification method in any of the above method embodiments by running the non-transitory software programs, instructions and modules stored in the memory 202, that is, can implement the entire process of Figure 2 .

[0155] The present application also provides a robot, please refer to Figure 10 , Figure 10 is a structural schematic diagram of a robot provided by the embodiments of the present application. The robot 300 comprises a laser radar 200 and a controller 301, wherein the laser radar 200 is communicatively connected to the controller 301, and the controller 301 is configured to send a ranging instruction to the laser radar 200 to enable the laser radar 200 to perform ranging. It can be understood that the ranging instruction can be sent to the robot 300 by an external terminal, and the ranging instruction is forwarded to the laser radar 200 by the controller 301. The external terminal can be a fixed terminal or a mobile terminal, such as a computer, a mobile phone, a tablet computer and other electronic devices, which are not limited herein.

[0156] The embodiments of the present application provide a computer readable storage medium, such as a memory including program code, which can be executed by a processor to complete the laser radar distorted point cloud angle identification method in the above embodiments. For example, the computer readable storage medium can be a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc Read-Only Memory, CDROM), a magnetic tape, a floppy disk and an optical data storage device, etc.

[0157] The embodiments of the present application provide a computer program product, which comprises one or more program codes stored in a computer readable storage medium. The processor of the laser radar reads the program code from the computer readable storage medium, and the processor executes the program code to complete the steps of the laser radar distorted point cloud angle identification method provided in the above embodiments.

[0158] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not to limit them; under the idea of the present application, the technical features in the above examples or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of the present application as described above, which are not provided in details for simplicity; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying the angle of a distorted point cloud using lidar, characterized in that, The method includes: Obtain the measurement range of the lidar and the position information of the support columns around the lidar; set the placement range and placement position of the calibration target according to the measurement range and the position information of the support columns; place the calibration target according to the placement range and placement position. Acquire the calibration point cloud generated by the lidar at the calibration target; Determine the angular range of the distorted point cloud caused by the support column in the calibration point cloud; Determining the angular range of the distorted point cloud caused by the support column in the calibration point cloud includes: determining whether there is a valid bit of a continuous point cloud in the calibration point cloud with a preset value; if so, taking the average angle of the continuous point cloud as the reference angle corresponding to the support column, and determining the angular range of the distorted point cloud caused by the support column in the calibration point cloud based on the reference angle; or If a preset value is set to determine whether there is a valid point cloud in the calibration point cloud, and if not, and no point cloud is generated at the location of the support column, then the absolute value of the distance difference between any two adjacent points in the calibration point cloud is calculated. The average angle of any two adjacent points whose absolute distance difference is greater than a preset threshold is taken as the reference angle corresponding to the support column. Based on the reference angle, the angle range of the distorted point cloud caused by the support column in the calibration point cloud is determined; or If a point cloud is generated at the location of the support column, the point cloud corresponding to the location of the support column is removed from the calibration point cloud to obtain a corrected calibration point cloud. The absolute value of the distance difference between any two adjacent points in the corrected calibration point cloud is calculated. The average angle of two adjacent points whose absolute distance difference is greater than a preset threshold is taken as the reference angle corresponding to the support column. The angle range of the distorted point cloud caused by the support column in the calibration point cloud is determined based on the reference angle.

2. The method according to claim 1, characterized in that, Determining the angular range of the distorted point cloud caused by the support column in the calibration point cloud based on the reference angle includes: Extend the reference angle to the left by a first preset angle to obtain a first angle region; extend the reference angle to the right by a second preset angle to obtain a second angle region; Based on the first angle region and the second angle region, the angle range of the distorted point cloud caused by the support column in the calibration point cloud is obtained.

3. The method according to claim 1, characterized in that, After determining the angular range of the distorted point cloud caused by the support column in the calibration point cloud, the method further includes: The point cloud data generated by the lidar during actual ranging is acquired, and the point cloud within the angular range of the distorted point cloud in the point cloud data is deleted or distance correction is performed on it to obtain the processed point cloud data.

4. The method according to claim 1, characterized in that, The calibration target is a closed or open polygon or ring.

5. A method for identifying the angle of a distorted point cloud using lidar, characterized in that, The method includes: Obtain the measurement range of the lidar and the position information of the support columns around the lidar; set the placement range and placement position of the calibration target according to the measurement range and the position information of the support columns; place the calibration target according to the placement range and placement position. Acquire the calibration point cloud generated by the lidar at the calibration target; Determine the angular range of the distorted point cloud caused by the support column in the calibration point cloud; Determining the angular range of the distorted point cloud in the calibration point cloud caused by the support column includes: Obtain the measured distance of each point in the calibration point cloud; Determine the actual distance between each point in the calibration point cloud and the lidar; Calculate the absolute value of the distance difference between the measured distance and the actual distance for each point in the calibration point cloud; Obtain the angle values ​​of continuous point clouds where the absolute value of the distance difference is greater than a distance threshold, and determine the angle range of the distorted point cloud caused by the support column in the calibration point cloud based on the angle values.

6. A method for identifying the angle of a distorted point cloud using lidar, characterized in that, The method includes: Obtain the measurement range of the lidar and the position information of the support columns around the lidar; set the placement range and placement position of the calibration target according to the measurement range and the position information of the support columns; place the calibration target according to the placement range and placement position. Acquire the calibration point cloud generated by the lidar at the calibration target; Determine the angular range of the distorted point cloud caused by the support column in the calibration point cloud; The calibration target is a circular target, and determining the angular range of the distorted point cloud caused by the support column in the calibration point cloud includes: Obtain the measured brightness of each point in the calibration point cloud; The standard brightness of the calibration point cloud is determined based on the measured brightness. Calculate the absolute value of the difference between the measured brightness and the standard brightness of each point in the calibration point cloud; Obtain the angle value of continuous point clouds where the absolute value of the brightness difference is greater than the brightness threshold, and determine the angle range of the distorted point cloud caused by the support column in the calibration point cloud based on the angle value.

7. A lidar distortion point cloud angle recognition device, characterized in that, include: The setting module is used to set the calibration target according to the position information of the support column, which is set around the lidar. The acquisition module is used to acquire the calibration point cloud generated by the lidar at the calibration target. The determination module is used to determine the angular range of the distorted point cloud caused by the support column in the calibration point cloud; The lidar distortion point cloud angle recognition device is used to perform the method as described in any one of claims 1 to 6.

8. A lidar, characterized in that, include: At least one processor, and The memory communicatively connected to the at least one processor, wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method according to any one of claims 1-6.

9. A robot, characterized in that, Including the lidar as described in claim 8.

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