Extrinsic Calibration of Camera and 2D Laser-Rangefinder with Various Chessboard Constrains

被引：0

作者：

Zhu F. ^{[1
]}

Fan J. ^{[1
]}

Huang Y. ^{[1
]}

Liu Y. ^{[2
]}

机构：

[1] School of Remote Sensing and Information Engineering, Wuhan University, Wuhan

[2] Beijing North-Star Technology Development Co. Ltd, Wuhan

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2019年 / 44卷 / 10期

基金：

中国国家自然科学基金;

关键词：

2D laser-rangefinder; Camera; Extrinsic calibration; Geometric constrains; Nonlinear optimization; V-shaped chessboard;

D O I：

10.13203/j.whugis20180022

中图分类号：

学科分类号：

摘要：

The combination of camera and 2D laser-rangefinder has been widely used in the fields of surveying, pilotless and robot. Extrinsic calibration between the two sensors is a prerequisite for fusing the texture information from images and depth information from the laser. To tackle this problem, a method of calibrating the extrinsic parameters between a camera and a 2D laser-rangefinder is proposed. This method establishes three geometric constraints between the laser scanning line and the V-shaped chessboard plane, including point to plane constraint, line to plane constrain and point to line constraint. The extrinsic parameters can be solved and optimized by redundant geometric constrains which help mitigate the impacts of noises in the laser points and image data. Experiments show that the proposed algorithm achieves higher accuracy and robustness than previous methods. And a quantitative evaluation criteria of the extrinsic parameters is proposed by calculating the distance between the intersecting point of the laser lines and the V-shaped chessboard line. © 2019, Editorial Board of Geomatics and Information Science of Wuhan University. All right reserved.

引用

页码：1524 / 1529and1537

共 18 条

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