基于标定板关键点的激光雷达与相机外参标定方法

Extrinsic Calibration Method of Lidar and Camera Based on Key Points of Calibration Board

针对micro electro mechanical system(MEMS)激光雷达与相机标定外参误差大的问题,提出了一种基于标定板关键点的外参标定方法。首先对多帧点云进行叠加预处理,然后基于Hough变换拟合标定板的边缘直线以确定关键点,最后设立关键点及法向量对应的约束条件,利用点面对应算法求出优化的标定外参。实验结果表明,所提方法可精确提取关键点,使得标定外参的平均误差相比现有的外参标定方法更低,提高了标定外参的精度。

Aiming at the problem of large extrinsic calibration error of micro electro mechanical system(MEMS) Lidar and camera, an extrinsic calibration method based on key points of calibration board is proposed. First, the multi-frame point clouds are superimposed for preprocessing, and then the edge line of the calibration board is fitted based on Hough transform to determine the key points. Finally, the constraints corresponding to the key points and normal vectors are set up, and the optimized calibration external parameters are obtained by using the point and plane correspondence algorithm. The experimental results show that the proposed method can accurately extract the key points, make the average error of calibrated external parameters lower than the existing external parameter calibration methods, and improve the accuracy of calibrated external parameters.