Extrinsic Calibration of Camera and 2D Laser-Rangefinder with Various Chessboard Constrains
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摘要: 面阵相机和线激光扫描仪的组合在移动测量、自动驾驶、机器人等领域中得到了广泛应用。影像纹理和激光深度数据融合的首要问题是两种传感器的外参标定。对此，提出了一种融合多种约束条件的相机和线激光外参标定算法。该算法建立激光扫描线与V型棋盘平面间的点-面、线-面、点-线等多种约束求解和优化激光与相机间的外参，减少了激光点和像点噪声对结果的影响。实验结果表明，该算法相较于之前的算法有更高的精度和鲁棒性。并通过计算激光交点到V型棋盘面交线的距离，提出了定量评价激光与相机外参精度的标准。Abstract: 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.
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