CN112859043B - Rotation shaft calibration method of self-rotation laser radar - Google Patents

Rotation shaft calibration method of self-rotation laser radar Download PDF

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CN112859043B
CN112859043B CN202110330490.1A CN202110330490A CN112859043B CN 112859043 B CN112859043 B CN 112859043B CN 202110330490 A CN202110330490 A CN 202110330490A CN 112859043 B CN112859043 B CN 112859043B
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calibration
point cloud
laser radar
cloud data
rotating
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CN112859043A (en
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陈方圆
余崇圣
李梦
董子乐
王建波
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Chongqing Zhizhi Technology Co ltd
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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
    • G01S7/481—Constructional features, e.g. arrangements of optical elements

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Optical Radar Systems And Details Thereof (AREA)

Abstract

The invention provides a rotating shaft calibration method of a self-rotating laser radar, which is characterized in that a self-rotating device is additionally arranged between the laser radar and a carrier, namely the laser radar rotates around the laser radar on the carrier, so that the original mode of acquiring surrounding space information from 'point' to 'line' is changed into the mode of acquiring surrounding space information from 'point' to 'line' to 'plane', and the surrounding space object point cloud information with higher density and wider visual angle range can be acquired.

Description

Rotation shaft calibration method of self-rotation laser radar
Technical Field
The invention relates to the field of laser radars, in particular to a rotating shaft calibration method of a self-rotating laser radar.
Background
In a plurality of fields such as unmanned automatic driving, unmanned aerial vehicle automatic mapping, robot, etc., mechanical laser radar is often selected as the sensor equipment who acquires the position appearance of surrounding space object, and it has high accuracy, long range finding, interference killing feature strong, small, characteristics such as light in weight. In the fields of common unmanned driving, surveying and mapping, robots and the like, a laser radar body and a carrier are generally fixedly connected, the relative static posture of the laser radar body and the carrier is kept, and the surrounding three-dimensional space object information is acquired by the movement of the carrier, the laser radar and the positioning navigation.
By adopting the method to acquire the three-dimensional information of the surrounding space, only the acquisition of the information of the surrounding space objects from the 'point' to the 'line' is realized, the defect of insufficient information quantity of the acquired point cloud information of the surrounding objects can occur, the high-precision real-scene modeling can not be realized, and the application scene is limited.
Disclosure of Invention
The invention provides a rotation axis calibration method of a self-rotation laser radar, which mainly solves the technical problems that: the insufficient acquisition amount of the point cloud information influences modeling accuracy.
In order to solve the technical problems, the invention provides a rotating shaft calibration method based on a self-rotating laser radar, which comprises the following steps:
The rotating end and the fixed end of the self-rotating laser radar are kept relatively static, point cloud data of a calibration ball are collected through the laser radar, the point cloud data are recorded as P 0, and the current rotating position is obtained as alpha 0 through an angle sensor;
the device for providing rotary power drives the rotary end to rotate by a relative angle, and the current rotary position alpha 1 is obtained by utilizing an angle sensor; the calibration ball, the fixed end and the earth are kept relatively static under the rotating position, point cloud data of the calibration ball are collected by using a laser radar, and the point cloud data are recorded as P 1;
Acquiring a rotation angle alpha=alpha 1-α0; fitting a calibration sphere by using a least square method based on the point cloud data P 0、P1 to obtain circle center positions C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration sphere;
Let the unit vector of the self axis around which the lidar is wound be n (n x,ny,nz) and pass through the point Q (X q,Yq,Zq) to construct a system of nonlinear equations as follows:
wherein the method comprises the steps of ,K＝1-cos(α),M＝nxXq+nyYq+nzZq,nx 2+ny 2+nz 2＝1;
From the known data C 0(X0,Y0,Z0)、C1(X1,Y1,Z1), α, the unit vector n (n x,ny,nz) of the rotation axis and the passing point Q coordinate Q (X q,Yq,Zq) can be obtained by performing a least square solution.
Further, the obtaining the circle center positions C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration sphere by fitting the calibration sphere using a least square method based on the point cloud data P 0、P1 includes:
E is the sum of squares of errors, the optimization target is that the E value is minimum, E is a function of X ', Y', Z ', X', Y ', Z' are circle center fitting coordinates, X i,Yi,Zi is spherical point cloud data of the calibration ball, N represents the sum of the number of denoised calibration ball spherical point clouds obtained by denoise filtering the point cloud data of the calibration ball obtained by acquisition, and E i is the difference between a calibration ball radius fitting estimated value and an actual value, and the sum is represented as follows:
ei(X',Y',Z',R)2＝(Xi-X')2+(Yi-Y')2+(Zi-Z')2-R2;
Wherein R is the actual radius value of the calibration sphere.
Further, before the calibration sphere is fitted by using the least square method to obtain the circle center position of the calibration sphere, denoising filtering is further included on the point cloud data P 0、P1.
The beneficial effects of the invention are as follows:
According to the method for calibrating the rotating shaft of the self-rotating laser radar, the self-rotating device is additionally arranged between the laser radar and the carrier, namely, the laser radar rotates around the laser radar on the carrier, so that the original mode of acquiring surrounding space information from 'point' to 'line' is changed into the mode of acquiring surrounding space information from 'point' to 'line' to 'surface', and the surrounding space object point cloud information with higher density and wider visual angle range can be acquired.
Drawings
FIG. 1 is a flow chart of a method for calibrating a rotating shaft according to the present invention;
FIG. 2 is a schematic view of a scene of the present invention when data is first collected;
fig. 3 is a schematic view of a scenario when data is acquired for the second time according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail by the following detailed description with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
By adopting the method of adding the self-rotating device between the carrier and the laser radar, the space point cloud which is denser and wider in visual angle range and more comprehensive in surrounding space information can be obtained, but the accuracy of obtaining the surrounding space object point cloud information can be influenced due to the mechanical installation accuracy, the dimensional accuracy of the whole laser radar shell and the like.
In order to solve the problem, the invention also provides a rotating shaft calibration method based on the self-rotating laser radar, which can efficiently and conveniently calibrate the self-rotating shaft of the laser radar. Please refer to fig. 1:
S401, as shown in fig. 2, is a schematic view of a scene when data is first acquired. One or more special calibration balls (radius is R) are prepared, the rotating end and the fixed end of the self-rotating device are kept relatively static, spherical point cloud data of the used calibration balls are collected by using a laser radar, the spherical point cloud data at the moment is recorded as P 0, and the current rotating position is obtained as alpha 0 by using an angle sensor.
S402, as shown in fig. 3, is a schematic view of a scene when data is acquired for the second time. The driving fixed end is used for providing rotary power equipment, the rotary end is rotated, and the used special calibration ball, the fixed end and the earth are kept relatively static in the process. And stopping rotating after the rotating end rotates by a certain relative angle.
And S403, after stopping rotating, acquiring spherical point cloud data of the used calibration ball again by using a laser radar, and recording that the spherical point cloud data at the moment is P 1 and the current rotating position is alpha 1.
S404, denoising and filtering the point cloud data P 0、P1 to obtain the point cloud data of the calibration ball used therein.
The denoising record broadcasting can adopt any existing mode, and can also be manually denoised, and the aim is that the obtained spherical point cloud data of the calibration sphere is more accurate.
S405, fitting the calibration balls by using a least square method by adopting point cloud data of the used calibration balls. The circle center positions C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration balls can be obtained.
Denoising and filtering the P 0 point cloud data, and fitting the circle center position C 0 of the used calibration sphere by using a least square method; denoising and filtering the P 1 point cloud data, and fitting the circle center position C 1 of the used calibration sphere by using a least square method.
The least square method optimization principle in step S405 is as follows:
E is the sum of squares of errors, the optimization target is that the E value is minimum, E is a function of X ', Y ', Z ', N represents the sum of the number of the point clouds of the denoising calibration sphere obtained by denoising and filtering the point cloud data of the calibration sphere, and E i is the difference between the calibration sphere radius fitting estimated value and the actual value, and the difference is represented as follows:
ei(X',Y',Z',R)2＝(Xi-X')2+(Yi-Y')2+(Zi-Z')2-R2
Wherein R is the actual radius value of the calibration sphere; x ', Y ', Z ' are circle center fitting coordinates, X i,Yi,Zi is sphere point cloud data of the calibration sphere, and the data thereof are obtained in step S405. Therefore, E (X ', Y', Z ') is an equation related to X', Y ', Z', and the values of X ', Y', Z 'when the minimum value of E can be obtained by respectively performing partial derivative on X', Y ', Z', namely the actual coordinates of the circle center are obtained, and a plurality of coordinates C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the circle center in the step S405 can be solved by adopting the method.
According to the two rotation positions, the rotation angle alpha of the laser radar rotating around the self axis can be calculated, and alpha=alpha 1-α0.
S406, according to the circle center position data C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration sphere, the rotation angle alpha around the self axis is described as follows: center position C 0(X0,Y0,Z0) rotates around an arbitrary axis by an angle α to obtain a new center position C 1(X1,Y1,Z1), the unit vector of the axis of the rotation shaft is n (n x,ny,nz), and passes through point Q (X q,Yq,Zq), where n x 2+ny 2+nz 2 =1.
The circle center positions C 0 and C 1 are in one-to-one correspondence, the rotation axis direction vector orthogonality is taken as a constraint condition, the rotation angle alpha is taken as a known condition, the least square solution is carried out on C 1＝TC0, and the coordinate representation of the rotation axis, the rotation axis direction vector n (n x,ny,nz) and the passing point coordinate Q (X q,Yq,Zq) can be obtained. The method specifically comprises the following steps:
The following set of nonlinear equations is constructed:
wherein the method comprises the steps of ,K＝1-cos(α),M＝nxXq+nyYq+nzZq,nx 2+ny 2+nz 2＝1;
S407, based on the known data C 0(X0,Y0,Z0)、C1(X1,Y1,Z1), α, the unit vector n (n x,ny,nz) of the rotation axis and the passing point Q coordinate Q (X q,Yq,Zq) can be obtained by performing least square solution. The least squares optimization principle in S407 is as follows:
e is the sum of squares of the errors, the optimization objective is that the E value is the smallest, E is a function of n x,ny,nz,Xq,Yq,Zq, and E i is the difference between the point-to-rotation axis distance fit estimate and the actual value, which is expressed as follows:
ei(nx,ny,nz,Xq,Yq,Zq)＝(L1-L'1)2
The actual distance from the center position C 1 to the rotation axis, L 1, can be expressed as the theoretical distance from the center position C 1 to the rotation axis, :L1(nx,ny,nz,Xq,Yq,Zq,X1,Y1,Z1),L′1, and ：L′1(nx,ny,nz,Xq,Yq,Zq,X0,Y0,Z0)., wherein X 0,Y0,Z0,X1,Y1,Z1 is already obtained in step seven, so e= (n x,ny,nz,Xq,Yq,Zq) is an equation for n x,ny,nz,Xq,Yq,Zq. And respectively solving the partial derivative function of n x,ny,nz,Xq,Yq,Zq for E, and forming an equation with the partial derivative function value equal to 0, so that the value corresponding to n x,ny,nz,Xq,Yq,Zq can be solved.
Thus, the calibration of the self-rotating laser radar is completed.
The method can be used for rapidly calibrating the rotation axis coordinate of the self-rotating mechanical laser radar, and the calibration precision is within 1 degree. By combining the self-rotating device with the existing positioning navigation algorithm (SLAM, GPS+RTK, etc.), the acquired surrounding space object information is more dense. When the laser radar is used for collecting surrounding space point cloud information, the point cloud data with wider view angle range can be obtained by using a self-rotating device method.
It will be appreciated by those skilled in the art that the steps of the invention described above may be implemented by general purpose computing devices, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, such that they may be stored on computer storage media (ROM/RAM, magnetic disk, optical disk) for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than what is shown or described herein, or they may be separately fabricated into individual integrated circuit modules, or a plurality of modules or steps in them may be fabricated into a single integrated circuit module. Therefore, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a further detailed description of the invention in connection with specific embodiments, and it is not intended that the invention be limited to such description. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.

Claims (3)

1. The rotating shaft calibration method based on the self-rotating laser radar is characterized by comprising the following steps of:
The rotating end and the fixed end of the self-rotating laser radar are kept relatively static, point cloud data of a calibration ball are collected through the laser radar, the point cloud data are recorded as P 0, and the current rotating position is obtained as alpha 0 through an angle sensor;
the device for providing rotary power drives the rotary end to rotate by a relative angle, and the current rotary position alpha 1 is obtained by utilizing an angle sensor; the calibration ball, the fixed end and the earth are kept relatively static under the rotating position, point cloud data of the calibration ball are collected by using a laser radar, and the point cloud data are recorded as P 1;
Acquiring a rotation angle alpha=alpha 1-α0; fitting a calibration sphere by using a least square method based on the point cloud data P 0、P1 to obtain circle center positions C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration sphere;
Let the unit vector of the self axis around which the lidar is wound be n (n x,ny,nz) and pass through the point Q (X q,Yq,Zq) to construct a system of nonlinear equations as follows:
wherein the method comprises the steps of ,K＝1-cos(α),M＝nxXq+nyYq+nzZq,nx 2+ny 2+nz 2＝1;
From the known data C 0(X0,Y0,Z0)、C1(X1,Y1,Z1), α, the unit vector n (n x,ny,nz) of the rotation axis and the passing point Q coordinate Q (X q,Yq,Zq) can be obtained by performing a least square solution.
2. The method for calibrating a rotation axis based on a self-rotating lidar according to claim 1, wherein the obtaining the center positions C 0(X0,Y0,Z0) and C 1(X1,Y1,Z1) of the calibration sphere by fitting the calibration sphere using a least square method based on the point cloud data P 0、P1 comprises:
E is the sum of squares of errors, the optimization target is that the E value is minimum, E is a function of X ', Y', Z ', X', Y ', Z' are circle center fitting coordinates, X i,Yi,Zi is spherical point cloud data of the calibration ball, N represents the sum of the number of denoised calibration ball spherical point clouds obtained by denoise filtering the point cloud data of the calibration ball obtained by acquisition, and E i is the difference between a calibration ball radius fitting estimated value and an actual value, and the sum is represented as follows:
ei(X',Y',Z',R)2＝(Xi-X')2+(Yi-Y')2+(Zi-Z')2-R2;
Wherein R is the actual radius value of the calibration sphere.
3. The method for calibrating a rotating shaft based on a self-rotating laser radar according to claim 1 or 2, wherein the method further comprises denoising and filtering point cloud data P 0、P1 before the calibration sphere is fitted by using a least square method to obtain the circle center position of the calibration sphere.
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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111337946A (en) * 2020-04-23 2020-06-26 湖南格纳微信息科技有限公司 Rotary full-field laser radar scanning system

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JP5891893B2 (en) * 2012-03-27 2016-03-23 株式会社デンソーウェーブ Laser radar equipment
EP3415945B1 (en) * 2017-06-12 2024-01-10 Aptiv Technologies Limited Method of determining the yaw rate of a target vehicle

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111337946A (en) * 2020-04-23 2020-06-26 湖南格纳微信息科技有限公司 Rotary full-field laser radar scanning system

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