CN116400334A - Calibration verification method and device for laser external parameters, electronic equipment and storable medium - Google Patents
Calibration verification method and device for laser external parameters, electronic equipment and storable medium Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 72
- 238000012795 verification Methods 0.000 title claims abstract description 46
- 230000005484 gravity Effects 0.000 claims abstract description 125
- 238000003860 storage Methods 0.000 claims abstract description 6
- 238000005070 sampling Methods 0.000 claims description 43
- 238000004590 computer program Methods 0.000 claims description 12
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- 238000001914 filtration Methods 0.000 claims description 8
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/42—Simultaneous measurement of distance and other co-ordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The embodiment of the application discloses calibration verification method, device, electronic equipment and storage medium of laser external parameters, fork truck outside is provided with 3D laser radar and tray, all is provided with the reflector panel on fork truck and the tray, and this method includes: obtaining point cloud data obtained by laser reflection of each reflector on the 3D laser radar; extracting partial point cloud data of each reflector from the point cloud data, and determining the gravity center point of each reflector according to the partial point cloud data of each reflector; determining the relative position relationship between the forklift and the pallet according to each gravity center point; and calibrating and verifying the relative position relation according to the pre-acquired position relation, and completing the calibrating and verifying process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation. By implementing the embodiment of the application, accurate laser external parameters can be obtained.
Description
Technical Field
The application relates to the technical field of laser radars, in particular to a calibration verification method and device for laser external parameters, electronic equipment and a storable medium.
Background
The lidar detects information such as the position of a target object by emitting a laser beam toward the target object and receiving the beam emitted from the target object. The laser radar can provide real and reliable target information for forklifts such as unmanned forklifts. In order to improve the sensing capability of a forklift such as an unmanned forklift to the surrounding environment, external parameter calibration is required to be carried out on a laser radar to obtain accurate laser external parameters. However, the existing scheme is mainly used for obtaining the laser external parameters by comparing the laser radar detection result with the actual measurement result, the mode is greatly influenced by the measurement precision, and the obtained laser external parameters are low in accuracy.
Disclosure of Invention
The embodiment of the application discloses a calibration verification method and device for laser external parameters, electronic equipment and a storable medium, which can reduce measurement errors and improve the accuracy of the obtained laser external parameters.
The first aspect of the embodiment of the application discloses a calibration verification method of laser external parameters, and fork truck outside is provided with 3D laser radar and tray, all be provided with the reflector panel on fork truck and the tray, the method includes:
obtaining point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector;
Extracting partial point cloud data of each reflector from the point cloud data, and determining the gravity center point of each reflector according to the partial point cloud data of each reflector;
determining the relative position relationship between the forklift and the pallet according to each gravity center point;
and calibrating and verifying the relative position relation according to the pre-acquired position relation, and completing the calibrating and verifying process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
The second aspect of this application embodiment discloses calibration verifying attachment of laser external parameters, and fork truck outside is provided with 3D laser radar and tray, all be provided with the reflector panel on fork truck and the tray, the device includes:
the data acquisition module is used for acquiring point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector;
the data processing module is used for extracting partial point cloud data of each reflector from the point cloud data and determining the gravity center point of each reflector according to the partial point cloud data of each reflector;
the relation determining module is used for determining the relative position relation between the forklift and the pallet according to each gravity center point;
And the calibration verification module is used for carrying out calibration verification on the relative position relation according to the pre-acquired position relation, and completing the calibration verification process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
The third aspect of the embodiment of the application discloses an electronic device, which comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor realizes any one of the calibration verification methods of the laser external parameters disclosed in the embodiment of the application.
A fourth aspect of the embodiments of the present application discloses a computer-readable storage medium storing a computer program, where the computer program when executed by a processor implements a calibration verification method for a laser external parameter disclosed in the embodiments of the present application.
Compared with the related art, the embodiment of the application has the following beneficial effects:
set up 3D laser radar in fork truck outside, set up the tray in fork truck outside, all be provided with the reflector panel on fork truck and the tray. And obtaining point cloud data obtained by laser reflection of each set reflector on the 3D laser radar, extracting partial point cloud data corresponding to each reflector from the point cloud data, and determining the gravity center point of each reflector according to the partial point cloud data corresponding to each reflector. And then determining the relative position relation between the forklift and the pallet according to the gravity center point of each reflector, and calibrating and verifying the determined relative position relation by the pre-acquired position relation. And under the condition that the pre-acquired position relation is the same as the determined relative position relation, ending and completing the calibration verification process of the laser external parameters. The accurate laser external parameters can be obtained, the measurement error in the process of measuring by using the 3D laser radar is greatly reduced, and the accuracy of measuring the position relationship in complex scenes such as factories, parks and the like is effectively improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is an application scenario diagram of a calibration verification method for laser external parameters disclosed in one embodiment;
FIG. 2 is a schematic flow chart of a calibration verification method for laser external parameters according to an embodiment of the disclosure;
FIG. 3 is a flow chart of another calibration verification method for laser external parameters according to an embodiment of the disclosure;
FIG. 4 is a schematic structural diagram of a calibration verification device for laser external parameters according to an embodiment of the disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be made clearly and completely with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments and figures herein are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
The embodiment of the application discloses a calibration verification method and device for laser external parameters, electronic equipment and a storable medium, which can reduce measurement errors and improve the accuracy of the obtained laser external parameters. The following will describe in detail.
Referring to fig. 1, fig. 1 is an application scenario diagram of a calibration verification method of laser external parameters disclosed in an embodiment. As shown in fig. 1, a forklift 10, pallet 20, 3D lidar 30, and reflector 40 may be included. The 3D lidar 30 and the pallet 20 are both disposed outside the forklift 10, which may be a manned forklift or an unmanned forklift, and the forklift 10 may include at least a central processing unit, a fork, and a directional wheel. The pallet 20 may be of different sizes or even different shapes, with the pallet 20 being positioned on an extension of the direction of the forks of the forklift. The 3D lidar 30 is located at the side of the forklift. The reflector 40 may be a rectangular reflector, and the reflector 40 is disposed on a pallet or a forklift.
The central processing unit in the forklift 10 or other devices acquires the point cloud data obtained by reflecting the laser emitted by each reflector 40 to the 3D laser radar 30, extracts part of the point cloud data of each reflector 40 from the point cloud data, and determines the center of gravity point of each reflector 40 according to the part of the point cloud data of each reflector 40. And then determining the relative position relation between the forklift 10 and the tray 20 according to each gravity center point, calibrating and verifying the determined relative position relation according to the pre-acquired position relation, and completing the calibration and verification process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
Referring to fig. 2, fig. 2 is a schematic flow chart of a calibration verification method of laser external parameters disclosed in an embodiment, the method can be applied to a forklift 10 in an application scene shown in fig. 1, a 3D laser radar and a tray are arranged outside the forklift, the tray is located on an extension line of a direction of a fork of the forklift, the 3D laser radar is located on a side edge of the forklift, and reflectors are arranged on the forklift and the tray. As shown in fig. 2, the method may include the steps of:
210. and obtaining point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector.
In the embodiment of the application, the 3D laser radar can emit laser signals towards the direction where the forklift and the tray are located, receive the reflected laser signals, and determine point cloud data according to the received reflected laser signals. The 3D lidar may transmit the determined point cloud data to a processor in the forklift. Or, the 3D lidar may transmit the received reflected laser signal to a processor in the forklift, so that the processor in the forklift determines point cloud data according to the received reflected laser signal. After the point cloud data is obtained, the forklift can screen the obtained point cloud data, for example, the point cloud data obtained by reflecting the laser sent by the 3D laser radar by each reflector is screened according to the intensity of the reflected laser signals, the time of receiving the reflected laser signals or the azimuth of the point cloud data on a forklift coordinate system.
220. And extracting partial point cloud data of each reflector from the point cloud data, and determining the gravity center point of each reflector according to the partial point cloud data of each reflector.
In the embodiment of the application, the forklift determines partial point cloud data corresponding to each reflector from the point cloud data obtained by reflecting the laser sent by the 3D laser radar by all the reflectors, namely, the point cloud data obtained by reflecting the laser of the 3D laser radar by each reflector. The forklift can specifically perform clustering processing on the point cloud data according to the position information of each sampling point in the obtained point cloud data, so as to determine a plurality of clusters, wherein the number of the determined clusters can be equal to that of the reflecting plates, and the set of the sampling points contained in each cluster is part of the point cloud data corresponding to one reflecting plate.
After the partial point cloud data corresponding to each reflector are determined, the forklift can determine the gravity center point of each reflector according to the position information of each sampling point in the partial point cloud data corresponding to the reflector. For each reflector, the forklift can specifically calculate a three-dimensional coordinate average value according to the three-dimensional coordinates of each sampling point in partial point cloud data corresponding to the reflector, and the average value is determined as the three-dimensional coordinate of the gravity center point of the reflector. Or, the forklift can determine the maximum abscissa and the minimum abscissa according to the three-dimensional coordinates of each sampling point in partial point cloud data corresponding to the reflector, so as to determine the average abscissa; determining the maximum ordinate and the minimum ordinate, thereby determining the average ordinate; and determining the largest vertical coordinate and the smallest vertical coordinate, thereby determining the average vertical coordinate. And determining the sampling point closest to the point distances corresponding to the average abscissa, the average ordinate and the average ordinate in each sampling point in partial point cloud data corresponding to the reflector as the gravity center point of the reflector.
230. And determining the relative position relationship between the forklift and the pallet according to each gravity center point.
In the embodiment of the application, the forklift determines the relative position relationship between the forklift and the tray according to the gravity center point of each reflector. For example, two reflectors a and B are disposed on the forklift, two reflectors C and D are also disposed on the pallet, and the distance between the two reflectors a and B on the forklift and the distance between the two reflectors C and D on the pallet are smaller than the distance between the reflector a or B on the forklift and the reflector C or D on the pallet. Therefore, the forklift can determine the distance between any two reflectors, specifically, the distance between a and B, the distance between a and C, the distance between a and D, the distance between B and C, the distance between B and D, and the distance between C and D according to the gravity center of the four reflectors A, B, C and D. The reflectors corresponding to the minimum two distances are respectively determined to be the reflectors arranged on the forklift and the reflectors arranged on the tray. For example, the smallest two distances are the distance between a and B, or the distance between C and D, then a and B can be considered to be reflectors provided on the forklift, and C and D can be reflectors provided on the pallet. Or A and B are reflectors arranged on the tray, and C and D are reflectors arranged on the forklift. As only the relative position relation between the forklift and the pallet is required to be determined, two groups of reflectors can be determined. Here, the forklift may determine the midpoint of the two center of gravity points of the reflectors a and B as the position where the forklift is located, and the midpoint of the two center of gravity points of the reflectors C and D as the position where the pallet is located. According to the two positions, the relative position relation between the forklift and the pallet can be determined.
240. And calibrating and verifying the relative position relation according to the pre-acquired position relation, and completing the calibrating and verifying process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
In the embodiment of the application, the forklift can detect the position of the tray through target sensing equipment such as a laser radar, a sensor or a depth camera and the like arranged on the forklift in advance, and determine the position relationship between the forklift and the tray, wherein the position relationship is the position relationship acquired in advance.
After determining the relative position relationship between the forklift and the pallet, calibrating and verifying the relative position relationship and the pre-acquired position relationship, specifically, determining the deviation condition between the relative position relationship and the pre-acquired position relationship, and if the deviation condition is within the allowable range, then the forklift can consider that the pre-acquired position relationship is the same as the relative position relationship. In this case, the forklift can end the calibration verification process of the laser external parameters.
In this application embodiment, the tray can be located on the extension line of fork position orientation of fork truck, and laser radar can be located the side of fork truck, and above-mentioned position setting mode can make laser radar gather the point cloud data of the reflector panel on fork truck and the tray better.
By adopting the embodiment, the forklift can acquire accurate laser external parameters, so that the measurement error in the process of measuring by using the 3D laser radar is greatly reduced, and the accuracy of measuring the position relationship in complex scenes such as factories, parks and the like is effectively improved.
In some embodiments, the forklift may also perform the following steps:
under the condition that the pre-acquired position relationship is different from the relative position relationship, the laser external parameters of the target sensing equipment on the forklift are adjusted so that the pre-acquired position relationship obtained by detecting the pallet through the target sensing equipment of the forklift is the same as the relative position relationship.
In the embodiment of the application, after the forklift obtains the relative position relationship between the forklift and the pallet, the relative position relationship can be compared with the position relationship between the forklift and the pallet obtained in advance, so as to determine whether the relative position relationship between the forklift and the pallet is the same as the position relationship between the forklift and the pallet obtained in advance. The forklift specifically can adopt 3D laser radar and other equipment arranged on the forklift to detect the pallet, and the position relationship between the forklift and the pallet is obtained in advance. If the relative position relationship between the forklift and the pallet is different from the pre-acquired position relationship between the forklift and the pallet, the forklift can continuously adjust the laser external parameters of the 3D laser radar and other devices arranged on the forklift according to the position relationship between the forklift and the pallet until the position relationship between the forklift and the pallet detected by the 3D laser radar and other devices arranged on the forklift is the same as the relative position relationship between the forklift and the pallet. For example, the positional relationship between the forklift and the pallet, which is obtained in advance by the 3D laser provided on the forklift, includes the three-dimensional coordinates (a 1, b1, c 1) of the forklift, the three-dimensional coordinates (D1, e1, f 1) of the pallet, and the angle theta1 between the forklift and the pallet under the forklift coordinate system. After the external 3D laser detection, the determined relative position relationship between the forklift and the pallet comprises three-dimensional coordinates (a 2, b2, c 2) of the forklift, three-dimensional coordinates (D2, e2, f 2) of the pallet and an angle theta2 between the forklift and the pallet under a forklift coordinate system. If the three-dimensional coordinates (a 1, b1, c 1) and the three-dimensional coordinates (a 2, b2, c 2), the three-dimensional coordinates (d 1, e1, f 1) and (d 2, e2, f 2), the angle theta1 and the angle theta2 are different in one or more groups, the relative positional relationship between the forklift and the pallet and the positional relationship between the forklift and the pallet acquired in advance can be considered to be different. Thus, the forklift can adjust the laser profile of the 3D laser provided on the forklift such that the three-dimensional coordinates (a 1, b1, c 1) are identical to the three-dimensional coordinates (a 2, b2, c 2), the three-dimensional coordinates (D1, e1, f 1) are identical to (D2, e2, f 2), and the angle theta1 is identical to the angle theta2.
By adopting the embodiment, the laser external parameters of the related equipment can be adjusted when the external parameter calibration verification result is not ideal, so that the follow-up measurement by adopting accurate laser external parameters is ensured, and the accuracy of the follow-up measurement is effectively improved.
In one embodiment, referring to fig. 3, fig. 3 is a flow chart of another calibration verification method of laser external parameters disclosed in one embodiment. The method can be applied to a forklift 10 in an application scene shown in fig. 1, a 3D laser radar and a tray are arranged outside the forklift, the tray is located on an extension line of the direction of a fork of the forklift, the 3D laser radar is located on the side edge of the forklift, at least two reflectors are respectively arranged on the fork of the forklift and the tray, reflectors are arranged at other positions of the forklift except the fork, and a plurality of reflectors located on the fork of the forklift and the tray are located on the same horizontal plane. As shown in fig. 3, the method may include the steps of:
310. and obtaining point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector, wherein the point cloud data at least comprises three-dimensional coordinates and reflection intensity of each sampling point.
In this embodiment of the present application, the point cloud data obtained by the forklift includes at least three-dimensional coordinates of each sampling point and reflection intensity of each sampling point. The three-dimensional coordinates may be three-dimensional coordinates in a ground coordinate system or three-dimensional coordinates in a forklift coordinate system.
320. And extracting partial point cloud data of each reflector from the point cloud data according to the reflection intensity of each sampling point.
In this application embodiment, because the reflector panel is better to the effect of laser reflection, and fork truck automobile body and tray body etc. are relatively poor to the effect of laser reflection, consequently, fork truck can be according to the effect to the laser reflection of 3D laser radar, namely the reflection of light intensity of every sampling point, confirms the partial point cloud data that every reflector panel corresponds. The forklift can be specifically provided with a preset reflection intensity threshold, sampling points with the reflection intensity larger than the threshold are screened out, and partial point cloud data of each reflection plate are determined. The partial point cloud data are the total undivided point cloud data of all reflectors. The number of the reflectors arranged on the fork can be one or more, the number of the reflectors arranged on the tray can be one or more, and the number of the reflectors arranged on the fork truck except the fork can be one or more. The reflective surface of each reflector faces the 3D lidar, and the reflective intensity of each reflector may be different. Through set up the reflector panel on fork and the tray at least at fork truck, can confirm the relative position between fork and the tray of fork truck effectively. In addition, the reflector plate is arranged at other positions of the forklift except for the fork, so that the forklift and the tray can be better distinguished, and the position of the forklift can be determined.
330. And clustering partial point cloud data of each reflector to determine a plurality of target point cloud sets.
In the embodiment of the application, the forklift can perform clustering processing on part of point cloud data of each obtained reflector through a clustering algorithm such as DBSCAN density clustering, and the point cloud data of all reflectors are separated, so that a plurality of target point cloud sets are determined, each target point cloud set corresponds to one reflector, and the number of the target point cloud sets can be kept consistent with the number of the reflectors. And the point cloud data contained in each target point cloud set is the actual point cloud data of the corresponding reflector. For example, the forklift obtains point cloud data including 1000 sampling points from the laser reflection of each reflector to the 3D laser radar, and the forklift screens out the point cloud data including 800 sampling points according to the reflection intensity of each sampling point, where the point cloud data including 800 sampling points is the point cloud data of each reflector. Then, the forklift processes point cloud data containing 800 sampling points by adopting DBSCAN density clustering, the 800 sampling points are separated to obtain 4 target point cloud sets a, b, c and d, each target point cloud set contains 200 sampling points, the target point cloud set a corresponds to the reflector A, and the target point cloud set a is actual point cloud data of the reflector A; the target point cloud set B corresponds to the reflector B, and the target point cloud set B is actual point cloud data of the reflector B; the target point cloud set C corresponds to the reflector C, and the target point cloud set C is actual point cloud data of the reflector C; the target point cloud set D corresponds to the reflector D, and the target point cloud set D is actual point cloud data of the reflector D.
In some embodiments, the clustering process performed on the partial point cloud data of each reflector in step 330 to determine a plurality of target point cloud sets may include the following steps:
filtering out isolated point cloud data in partial point cloud data of each reflector by adopting a statistical filtering mode to obtain optimized partial point cloud data of each reflector;
clustering the optimized partial point cloud data of each reflector to determine a plurality of target point cloud sets.
In this embodiment of the present application, after determining partial point cloud data of each reflector, the forklift may process the target point cloud set in a statistical filtering manner, so as to filter out point cloud data that may be an error or an outlier, that is, isolated point cloud data. Specifically, the forklift can calculate the average distance from each sampling point to k nearest sampling points, the distances of all sampling points in part of point cloud data should form Gaussian distribution, and the forklift can remove sampling points outside the variance according to given mean and variance, so that the filtering of isolated point cloud data in part of point cloud data is realized, and the optimized part of point cloud data of each reflector is obtained. Then, the forklift can cluster the optimized partial point cloud data of each reflector through a clustering algorithm such as DBSCAN density clustering, and the point cloud data of all reflectors are separated, so that a plurality of target point cloud sets are determined, each target point cloud set corresponds to one reflector, and the number of the target point cloud sets and the number of the reflectors can be kept consistent. And the point cloud data contained in each target point cloud set is the actual point cloud data of the corresponding reflector.
By adopting the embodiment, the optimization of the point cloud data can be realized, the influence of uncorrelated point cloud data on the determination of the gravity center and the determination of the relative position relationship between the forklift and the pallet is avoided, and the accuracy of the calibration and verification process is improved.
340. And determining the gravity center point corresponding to each target point cloud set according to the aggregation position of each target point cloud set.
In the embodiment of the application, the forklift can determine the gravity center point corresponding to each target point cloud set, namely the corresponding reflector, according to the aggregation position of each target point cloud set. For example, the target point cloud set a corresponding to the reflector a includes 200 sampling points, the forklift may perform an average process on three-dimensional coordinates of the 200 sampling points, specifically, calculate average values of abscissa, ordinate and ordinate of the 200 sampling points, respectively, to obtain a three-dimensional coordinate (x 1, y1, z 1) composed of an average value x1 of the abscissa, an average value y1 of the ordinate and an average value z1 of the ordinate, where the three-dimensional coordinate (x 1, y1, z 1) is a center of gravity point of the reflector a, or a center of gravity point corresponding to the target point cloud set a. The forklift truck can also screen out 200 sampling points with the smallest abscissa and the largest abscissa from the target point cloud set a, calculate the average abscissa x1 according to the abscissas of the two sampling points, screen out the sampling point with the smallest ordinate and the largest ordinate, calculate the average ordinate y1 according to the ordinates of the two sampling points, screen out the sampling point with the smallest ordinate and the sampling point with the largest ordinate, calculate the average vertical coordinate z1 according to the vertical coordinates of the two sampling points, and the three-dimensional coordinates (x 1, y1, z 1) formed by the three average values are the gravity center point of the reflector A, or the gravity center point corresponding to the target point cloud set a. The forklift can directly determine the gathering positions of 200 sampling points according to the distribution of 200 sampling points contained in the target point cloud set a, and the sampling points corresponding to the gathering positions are determined to be the gravity center point of the reflector A or the gravity center point corresponding to the target point cloud set a.
350. And determining the gravity center point of each reflector according to the height value of each gravity center point.
In this application embodiment, the reflector panel sets up respectively on fork truck and tray, and the reflector panel not only needs to set up on fork truck's fork, still needs to set up on other positions of fork truck except the fork truck, like automobile body, wheel or portal etc. the reflector panel that sets up on fork truck's fork is two at least, and the reflector panel that sets up on the tray is two at least also, and the reflector panel that sets up on other positions of fork truck except the fork is one at least. The reflector plate that sets up on fork truck and the reflector plate that sets up on the tray can be in same horizontal plane, and the height that sets up the reflector plate in other positions except fork truck can be greater than the height of the reflector plate that sets up on fork truck's fork and on the tray, also can be less than the height of the reflector plate that sets up on fork truck's fork and on the tray. The forklift can distinguish whether each gravity point is the gravity point of the reflector arranged at other positions on the forklift or the gravity point of the reflector arranged on the fork of the forklift and the tray according to each determined gravity point. The method comprises the steps that a reflector on a fork of a forklift and a reflector on a tray are arranged on the same horizontal plane, whether the reflector is arranged on the fork or the tray can be better determined according to the position relation between the forklift and the tray, and interference of point cloud data at other height positions can be eliminated; in addition, at least two reflectors are arranged on the fork of the forklift and at least two reflectors are arranged on the tray, so that the position conditions of the forklift and the tray are better reflected by the point cloud data, and the accuracy of the subsequent calibration and verification process is improved;
In addition, the reflector is arranged at other positions on the forklift, and the reflectors at other positions on the forklift, the pallet fork and the reflectors on the pallet are not in the same horizontal plane, so that the point cloud data better reflect the conditions of different positions on the forklift, and meanwhile, the reflectors on the pallet fork and the reflectors at other positions on the forklift can be better distinguished according to the difference of heights.
For example, reflectors a and B disposed on the forks of a forklift are on the same level as reflectors C and D disposed on the pallet, that is, reflectors A, B, C and D are equal in height. A reflector E is also arranged on the forklift body, and the height of the reflector E is larger than that of the reflectors A, B, C and D. The forklift truck can determine one gravity point with the highest height according to the height of each gravity point, specifically, the vertical coordinate in the three-dimensional coordinate of each gravity point, wherein the gravity point with the highest height is the gravity point of the reflector E, and other gravity points with the same height are the gravity points of the reflectors A, B, C and D respectively. And because the distance between the reflector arranged on the body of the forklift and the reflector arranged on the fork is obviously smaller than the distance between the reflector arranged on the body of the forklift and the reflector arranged on the tray, the forklift can determine the closest two-distance gravity points and the farthest two-distance gravity points according to the distances between the gravity points of the reflector E and the other four gravity points, and then the closest two-distance gravity points can be determined as the gravity points of the reflectors A and B arranged on the fork, and the farthest two-distance gravity points can be determined as the gravity points of the reflectors C and D arranged on the tray. Wherein, the focus point of the reflector panel that sets up on fork truck's fork is first focus point, and the focus point of the reflector panel that sets up on the tray is the second focus point.
By adopting the embodiment, partial point cloud data of all the reflectors and the target point cloud sets corresponding to each reflector can be accurately screened, so that the accuracy of the determined center of gravity of each reflector is improved, and the accuracy of the calibration and verification process is effectively improved. In addition, according to the height difference between the reflector arranged at other positions except the fork of the forklift and other reflectors and according to the distance characteristics between the reflector arranged at other positions except the fork of the forklift and other reflectors, whether the reflectors are arranged on the forklift or the pallet is effectively distinguished, the belongings of each gravity center point are distinguished, and the relative position relation between the subsequent forklift and the pallet can be more accurately determined.
In some embodiments, the other location is outboard of the orienting wheel, which is lower in height than the forks.
The process of determining the center of gravity of each reflector according to the height value of each center of gravity in step 350 may include the following steps:
determining a gravity center point with the minimum height value as a gravity center point of a reflector arranged outside the directional wheel, and determining a target point cloud set corresponding to the gravity center point of the reflector arranged outside the directional wheel as the reflector arranged outside the directional wheel;
And determining the point clouds of the reflectors arranged on the pallet according to the distance between the reflectors arranged on the outer sides of the directional wheels and other reflectors, wherein the point clouds of the two reflectors closest to the reflectors arranged on the outer sides of the directional wheels are the point clouds of the reflectors arranged on the pallet, and the point clouds of the other reflectors are the point clouds of the reflectors arranged on the pallet.
For example, two reflectors a and B are disposed on the forks of a forklift, two reflectors C and D are disposed on the pallet, and a reflector E is disposed outside the directional wheels of the forklift. Wherein, reflector A and B set up respectively in the symmetry position of fork, reflector C and D set up respectively in the symmetry position of tray both sides, and reflector A, B, C and D highly agree, because the height of directional wheel is less than fork height, therefore reflector E's height is less than the height of other four reflectors. The reflector may be a square reflector with a thickness of 5cm x 5cm, and all the reflectors are oriented in the same direction. In addition, the tray is arranged at a position 2m away from the fork root in the fork direction of the forklift. The 3D laser radar sets up in the one side of reflector panel reflection of light face, and the horizontal distance of 3D laser radar and fork truck can be 2m, highly is 18cm. After the five gravity points are determined, the forklift can determine the gravity point with the lowest height according to the heights of the five gravity points, and the gravity point is the gravity point of the reflecting plate E, namely the gravity point of the reflecting plate arranged on the outer side of the directional wheel. Then, the forklift can determine that the target point cloud set E corresponding to the gravity center point of the reflector arranged on the outer side of the directional wheel is the reflector arranged on the outer side of the directional wheel, that is, the sampling points contained in the target point cloud set E form the reflector E arranged on the outer side of the directional wheel. Because the distance between the fork and the directional wheel is closer than the distance between the fork and the tray, the fork truck can determine the point cloud of the reflector arranged on the fork and the point cloud of the reflector arranged on the tray according to the distance between the reflector arranged on the outer side of the directional wheel and other reflectors. The forklift can determine the distance between the gravity center point of the reflector E and other gravity center points as the distance between the reflector arranged on the outer side of the directional wheel and other reflectors; the fork truck can also calculate the distance between each sampling point contained in the target point cloud set e and a gravity center point, and the obtained minimum distance is the distance between the reflector corresponding to the gravity center point and the reflector arranged on the outer side of the directional wheel. The distance between the reflector arranged outside the directional wheel and other reflectors is determined accordingly. After the distance between the reflector E and the other four reflectors is determined, determining two reflectors closest to the reflector E as reflectors A and B by the forklift, wherein the point clouds of the two reflectors are the point clouds of the reflectors arranged on the fork; and the fork truck determines other reflectors as reflectors C and D, and the point clouds of the two reflectors are the point clouds of the reflectors arranged on the tray. Two reflectors are arranged at the symmetrical positions of the tray, and two reflectors are arranged at the symmetrical positions of the fork, so that the coordinates of a pair of reflectors on the fork on one axis are the same, the coordinates of a pair of reflectors on the tray on one axis are the same, and the condition that the point cloud is on the other two axes of the three-dimensional coordinate system can be well determined. In addition, the directional wheel is a key position on the forklift, and the calibration process can be verified by combining point cloud data of important parts on the forklift through arranging the reflecting plate at the position.
By adopting the embodiment, the reflector arranged on the outer side of the directional wheel and the corresponding point cloud can be rapidly and accurately determined, each reflector and the corresponding point cloud are accurately determined based on the reflector arranged on the outer side of the directional wheel, the accuracy of the identified reflector is improved, and the accuracy of the subsequent calibration and verification process is further improved.
360. And determining a first linear equation according to at least two first gravity points of at least two reflecting plates on the forklift.
370. And determining a second linear equation according to at least two second center points of at least two reflecting plates on the tray.
380. And determining the relative position relationship between the forklift and the pallet according to the first linear equation, the second linear equation, at least two first gravity points and at least two second gravity points.
In the embodiment of the application, in the process of determining the relative relationship between the forklift and the pallet, the forklift can specifically determine a linear equation, namely a first linear equation, according to the determined gravity center points of at least two reflectors arranged on the forklift, that is, at least two first gravity center points. Meanwhile, the forklift can determine another linear equation, namely a second linear equation, according to the determined gravity center points, namely at least two second gravity center points, of the at least two reflecting plates arranged on the tray. And then the forklift can determine the relative position relationship between the forklift and the pallet according to the determined two linear equations, at least two first gravity points and at least two second gravity points. The forklift can specifically determine the intercept and the slope of the straight line where the two first gravity points are located according to the three-dimensional coordinates of the two first gravity points, so as to determine a first straight line equation; and determining the intercept and the slope of the straight line where the two second gravity center points are located according to the three-dimensional coordinates of the two second gravity center points by the forklift, so as to determine a second straight line equation.
For example, the reflectors disposed on the forks of the forklift are a and B, respectively, and the reflectors disposed on the pallet are C and D, respectively. The forklift determines that the gravity center point of the reflector A is (x 1, y1, z 1), the gravity center point of the reflector B is (x 2, y2, z 2), the gravity center point of the reflector C is (x 3, y3, z 3), and the gravity center point of the reflector D is (x 4, y4, z 4). According to the two first gravity points (x 1, y1, z 1) and (x 2, y2, z 2) of the reflectors A and B, the forklift determines the intercept and the slope of the straight line where the first gravity points (x 1, y1, z 1) and (x 2, y2, z 2) are located and each coordinate axis respectively, and calculates a first straight line equation L1 according to the determined intercept and slope; the forklift truck further determines the intercept and the slope of the straight line where the second center points (x 3, y3, z 3) and (x 4, y4, z 4) are located and each coordinate axis according to the two second center points (x 3, y3, z 3) and (x 4, y4, z 4) of the light reflecting plates C and D, and calculates a second straight line equation L2 according to the determined intercept and slope. After determining the straight line equations L1 and L2, the forklift can calculate the distance between two straight lines, determine the distance between the forklift and the tray, and then determine the azimuth between the forklift and the tray according to the position relationship between the two first gravity center points and the two second gravity center points, wherein the position and the azimuth are combined to determine the relative position relationship between the forklift and the tray.
By adopting the embodiment, the accuracy of the determined relative position relationship between the forklift and the tray is further improved by determining the linear equation and combining the determined gravity center point corresponding to each reflector, so that the accuracy of calibration and verification is improved.
390. And calibrating and verifying the relative position relation according to the pre-acquired position relation, and completing the calibrating and verifying process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
In some embodiments, the determining the relative positional relationship between the forklift and the pallet in step 380 according to the first linear equation, the second linear equation, at least two first center of gravity points, and at least two second center of gravity points may include the following steps:
determining a first slope corresponding to the first linear equation and a second slope corresponding to the second linear equation;
determining a first center point according to at least two first center points;
determining a second center point according to the at least two second center points;
and determining the relative position relationship between the forklift and the pallet according to the first slope, the second slope, the first center point and the second center point.
In the embodiment of the application, in the process of determining the relative relationship between the forklift and the pallet, the forklift can specifically determine a linear equation, namely a first linear equation, according to the determined gravity center points of at least two reflectors arranged on the forklift, that is, at least two first gravity center points. Meanwhile, the forklift can determine another linear equation, namely a second linear equation, according to the determined gravity center points, namely at least two second gravity center points, of the at least two reflecting plates arranged on the tray. The truck may then determine the slope of the first linear equation, i.e., the first slope and the second slope, e.g., ax+by+c=0, and the slope corresponding to the first linear equation, i.e., the first slope, is k= -a/B. The forklift further determines a first center point according to at least two first center points and a second center point according to at least two second center points in addition to the first slope and the second slope. The first center point may be obtained by calculating an average value of three-dimensional coordinates of all the first center points, and the second center point may be obtained by calculating an average value of three-dimensional coordinates of all the second center points, which will not be described herein. And determining the relative position relationship between the forklift and the pallet according to the obtained first slope, second slope, first center point and second center point. The forklift can determine the angle between the forklift and the pallet under the forklift coordinate system according to the obtained first slope and second slope, and the forklift determines the distance between the forklift and the pallet according to the obtained first center point and second center point. And determining the angle and the distance between the forklift and the pallet as the relative position relationship between the forklift and the pallet.
By adopting the embodiment, the angle between the forklift and the tray can be accurately determined by adopting the slope between the two linear equations, the distance between the forklift and the tray can be accurately determined by adopting the center point between the two center-of-gravity points, and the distance is used as the relative position relationship between the forklift and the tray, so that the accuracy of the determined relative position relationship between the forklift and the tray is further improved, and the calibration verification accuracy is further improved.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a laser external parameter calibration and verification device disclosed in an embodiment, the laser external parameter calibration and verification device can be applied to a forklift 10 in an application scene shown in fig. 1, a 3D laser radar and a tray are arranged outside the forklift, the tray is located on an extension line of a direction of a fork of the forklift, the 3D laser radar is located at a side edge of the forklift, and reflectors are arranged on the forklift and the tray. As shown in fig. 4, the calibration verification device 400 for laser external parameters may include: a data acquisition module 410, a data processing module 420, a relationship determination module 430, and a calibration verification module 440.
The data acquisition module 410 is configured to acquire point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector;
The data processing module 420 is configured to extract partial point cloud data of each reflector from the point cloud data, and determine a center of gravity point of each reflector according to the partial point cloud data of each reflector;
the relationship determining module 430 is configured to determine a relative positional relationship between the forklift and the pallet according to each center of gravity point;
the calibration verification module 440 is configured to perform calibration verification on the relative positional relationship according to the pre-acquired positional relationship, and complete the calibration verification process of the laser external parameter under the condition that the pre-acquired positional relationship is the same as the relative positional relationship.
In some embodiments, at least two reflectors are disposed on the forks and the pallet of the forklift, respectively.
The relationship determination module 430 is further configured to:
determining a first linear equation according to at least two first gravity points of at least two reflecting plates on the forklift;
determining a second linear equation according to at least two second center points of at least two reflecting plates on the tray;
and determining the relative position relationship between the forklift and the pallet according to the first linear equation, the second linear equation, at least two first gravity points and at least two second gravity points.
In some embodiments, the relationship determination module 430 is further configured to:
Determining a first slope corresponding to the first linear equation and a second slope corresponding to the second linear equation;
determining a first center point according to at least two first center points;
determining a second center point according to the at least two second center points;
and determining the relative position relationship between the forklift and the pallet according to the first slope, the second slope, the first center point and the second center point.
In some embodiments, the forklift is provided with a reflector at other positions than the forks, and the point cloud data at least comprises three-dimensional coordinates of each sampling point and the reflection intensity.
The data processing module 420 is further configured to:
extracting partial point cloud data of each reflector from the point cloud data according to the reflection intensity of each sampling point;
clustering partial point cloud data of each reflector to determine a plurality of target point cloud sets;
according to the gathering position of each target point cloud set, determining a gravity center point corresponding to each target point cloud set;
and determining the gravity center point of each reflector according to the height value of each gravity center point.
In some embodiments, the plurality of reflectors on the forks and the pallet of the forklift are on the same horizontal plane; the other positions are the outer sides of the directional wheels, and the height of the directional wheels is lower than that of the fork.
The data processing module 420 is further configured to:
determining a gravity center point with the minimum height value as a gravity center point of a reflector arranged outside the directional wheel, and determining a target point cloud set corresponding to the gravity center point of the reflector arranged outside the directional wheel as the reflector arranged outside the directional wheel;
and determining the point clouds of the reflectors arranged on the pallet according to the distance between the reflectors arranged on the outer sides of the directional wheels and other reflectors, wherein the point clouds of the two reflectors closest to the reflectors arranged on the outer sides of the directional wheels are the point clouds of the reflectors arranged on the pallet, and the point clouds of the other reflectors are the point clouds of the reflectors arranged on the pallet.
In some embodiments, the data processing module 420 is further configured to:
filtering out isolated point cloud data in partial point cloud data of each reflector by adopting a statistical filtering mode to obtain optimized partial point cloud data of each reflector;
clustering the optimized partial point cloud data of each reflector to determine a plurality of target point cloud sets.
In some embodiments, the calibration verification device of the laser external parameter shown in fig. 4 further includes:
and the external parameter adjusting module 450 is configured to adjust the external parameters of the laser of the 3D laser radar when the pre-acquired positional relationship is different from the relative positional relationship, so that the pre-acquired positional relationship obtained by detecting the pallet by the target sensing device of the forklift is the same as the relative positional relationship.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment. As shown in fig. 5, the electronic device 500 may include:
a memory 510 storing executable program code.
A processor 520 coupled to the memory 510.
The processor 520 invokes the executable program code stored in the memory 510 to execute any of the calibration verification methods of the laser external parameters disclosed in the embodiments of the present application.
It should be noted that, the electronic device shown in fig. 5 may further include components not shown, such as a power supply, an input key, a camera, a speaker, a screen, an RF circuit, a Wi-Fi module, a bluetooth module, etc., which are not described in detail in this embodiment.
The embodiment of the application discloses a computer readable storage medium which stores a computer program, wherein the computer program enables a computer to execute any one of the calibration verification methods of laser external parameters disclosed in the embodiment of the application.
Embodiments of the present application disclose a computer program product comprising a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform any of the laser external reference calibration verification methods disclosed in the embodiments of the present application.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art will also appreciate that the embodiments described in the specification are all alternative embodiments and that the acts and modules referred to are not necessarily required in the present application.
In various embodiments of the present application, it should be understood that the size of the sequence numbers of the above processes does not mean that the execution sequence of the processes is necessarily sequential, and the execution sequence of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-accessible memory. Based on such understanding, the technical solution of the present application, or a part contributing to the prior art or all or part of the technical solution, may be embodied in the form of a software product stored in a memory, including several requests for a computer device (which may be a personal computer, a server or a network device, etc., in particular may be a processor in the computer device) to perform part or all of the steps of the above-mentioned method of the various embodiments of the present application.
Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the above embodiments may be implemented by a program that instructs associated hardware, the program may be stored in a computer readable storage medium including Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disk Memory, magnetic disk Memory, tape Memory, or any other medium that can be used for carrying or storing data that is readable by a computer.
The calibration verification method, device, electronic equipment and storable medium of the laser external parameters disclosed in the embodiments of the present application are described in detail, and specific examples are applied to illustrate the principles and embodiments of the present application, and the description of the above embodiments is only used to help understand the method and core idea of the present application. Meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope according to the ideas of the present application, the present disclosure should not be construed as limiting the present application in view of the above description.
Claims (10)
1. The utility model provides a calibration verification method of laser external parameters, its characterized in that, fork truck outside is provided with 3D laser radar and tray, all be provided with the reflector panel on fork truck and the tray, the method includes:
obtaining point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector;
extracting partial point cloud data of each reflector from the point cloud data, and determining the gravity center point of each reflector according to the partial point cloud data of each reflector;
determining the relative position relationship between the forklift and the pallet according to each gravity center point;
And calibrating and verifying the relative position relation according to the pre-acquired position relation, and completing the calibrating and verifying process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
2. The method according to claim 1, wherein at least two reflectors are respectively arranged on the pallet and the fork of the forklift;
the determining the relative positional relationship between the forklift and the pallet according to each gravity center point comprises the following steps:
determining a first linear equation according to at least two first gravity points of at least two reflecting plates on the forklift;
determining a second linear equation according to at least two second center points of at least two reflecting plates on the tray;
and determining the relative position relationship between the forklift and the pallet according to the first linear equation, the second linear equation, the at least two first gravity points and the at least two second gravity points.
3. The method of claim 2, wherein determining the relative positional relationship between the forklift and pallet based on the first linear equation, the second linear equation, the at least two first points of gravity, and the at least two second points of gravity comprises:
Determining a first slope corresponding to the first linear equation and a second slope corresponding to the second linear equation;
determining a first center point according to the at least two first center points;
determining a second center point according to the at least two second center points;
and determining the relative position relationship between the forklift and the pallet according to the first slope, the second slope, the first center point and the second center point.
4. The method according to claim 2, wherein the forklift is provided with a reflector at other positions than the forks, and the point cloud data at least comprises three-dimensional coordinates of each sampling point and reflection intensity;
the extracting part of the point cloud data of each reflector from the point cloud data, and determining the center of gravity point of each reflector according to the part of the point cloud data of each reflector comprises the following steps:
extracting partial point cloud data of each reflector from the point cloud data according to the reflection intensity of each sampling point;
clustering partial point cloud data of each reflector to determine a plurality of target point cloud sets;
according to the gathering position of each target point cloud set, determining a gravity center point corresponding to each target point cloud set;
And determining the gravity center point of each reflector according to the height value of each gravity center point.
5. The method of claim 4, wherein the other location is outside of a orienting wheel having a height that is lower than the height of the forks; the determining the gravity center point of each reflector according to the height value of each gravity center point comprises the following steps:
determining a gravity center point with the minimum height value as a gravity center point of a reflector arranged outside the directional wheel, and determining a target point cloud set corresponding to the gravity center point of the reflector arranged outside the directional wheel as the reflector arranged outside the directional wheel;
and determining the point clouds of the reflectors arranged on the pallet according to the distance between the reflectors arranged on the outer sides of the directional wheels and other reflectors, wherein the point clouds of two reflectors closest to the reflectors arranged on the outer sides of the directional wheels are the point clouds of the reflectors arranged on the pallet, and the point clouds of other reflectors are the point clouds of the reflectors arranged on the pallet.
6. The method of claim 4, wherein clustering the partial point cloud data of each reflector to determine a plurality of target point cloud sets comprises:
Filtering out isolated point cloud data in partial point cloud data of each reflector by adopting a statistical filtering mode to obtain optimized partial point cloud data of each reflector;
clustering the optimized partial point cloud data of each reflector to determine a plurality of target point cloud sets.
7. The method according to any one of claims 1-6, further comprising:
under the condition that the pre-acquired position relation is different from the relative position relation, adjusting the laser external parameters of the 3D laser radar so that the pre-acquired position relation obtained by detecting the tray through the target sensing equipment of the forklift is the same as the relative position relation; the target sensing equipment is the sensing equipment with completed calibration.
8. Calibration verification device of laser exoparameter, its characterized in that, fork truck outside is provided with 3D laser radar and tray, all be provided with the reflector panel on fork truck and the tray, the device includes:
the data acquisition module is used for acquiring point cloud data obtained by reflecting laser sent by the 3D laser radar by each reflector;
The data processing module is used for extracting partial point cloud data of each reflector from the point cloud data and determining the gravity center point of each reflector according to the partial point cloud data of each reflector;
the relation determining module is used for determining the relative position relation between the forklift and the pallet according to each gravity center point;
and the calibration verification module is used for carrying out calibration verification on the relative position relation according to the pre-acquired position relation, and completing the calibration verification process of the laser external parameters under the condition that the pre-acquired position relation is the same as the relative position relation.
9. An electronic device comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, causes the processor to implement the method of any of claims 1 to 7.
10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any one of claims 1 to 7.
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