基于手眼模型的三维激光雷达外参数标定

Calibration of extrinsic parameters for three-dimensional lidar based on hand-eye model

无人车三维激光雷达与GPS/INS组合导航系统融合使用,需要对两者之间的相对位姿进行标定。针对车辆运动过程点云畸变的现象,提出了一种单帧点云中激光扫描点坐标修正方法。针对标定问题,建立了标定模型,提出了一种基于ICP算法和手眼标定模型及最小二乘法进行外参数标定的方法。通过蒙特卡罗仿真实验,对该方法的有效性和精度进行了仿真和验证。在实验室JJUV-6无人车平台上进行标定试验,得到两者之间的三维位姿关系。对比标定前后三维点云重建效果,点云重叠度接近于配准效果。基于应用的目的,基本满足二维地图构建和三维环境重建的需求。

It is necessary to calibrate the relative pose between the three-dimensional（3D） lidar and the GPS/INS integrated navigation system for their combination. Because of the phenomenon of point cloud distortion in vehicle moving process, a method of coordinate correction for laser scanning point in single frame point cloud is proposed. Aiming at the calibration problem, a method of extrinsic parameter calibration is proposed, based on ICP algorithm, hand-eye calibration model, and least squares method. Monte Carlo simulation results show that the algorithm is accurate and effective. The calibration experiment is carried out on the unmanned vehicle laboratory JJUV-6, and the 3D relative pose relations are obtained. It shows that after calibration the effect of 3D point clouds reconstruction is better, and the overlapping degree of point clouds is close to the registration effect. For the purpose of applications, it can meet the needs of 2D map construction and 3D environment reconstruction.