论文标题
LIDAR和GNSS/INS之间用于自动驾驶的外部校准方法
An Extrinsic Calibration Method between LiDAR and GNSS/INS for Autonomous Driving
论文作者
论文摘要
准确可靠的传感器校准对于在自动驾驶中融合激光雷达和惯性测量至关重要。本文提出了一种新型的三阶段外部校准方法，用于自动驾驶，以示内行动和GNSS/ins/ins。第一阶段可以通过点云表面特征快速校准传感器之间的外部参数，以便可以将外部范围从大的初始误差范围缩小到很小的时间内的较小误差范围。第二阶段可以基于激光映射空间占用率进一步校准外部参数，同时消除运动失真。在最后阶段，校正由自动驾驶汽车的平面运动引起的Z轴误差，并最终获得了准确的外部参数。具体而言，此方法利用环境中的平面特征，使得快速进行校准成为可能。现实世界数据集的实验结果证明了我们方法的可靠性和准确性。这些代码是在GitHub网站上开源的。代码链接是https://github.com/opencalib/lidar2ins。
Accurate and reliable sensor calibration is critical for fusing LiDAR and inertial measurements in autonomous driving. This paper proposes a novel three-stage extrinsic calibration method between LiDAR and GNSS/INS for autonomous driving. The first stage can quickly calibrate the extrinsic parameters between the sensors through point cloud surface features so that the extrinsic can be narrowed from a large initial error to a small error range in little time. The second stage can further calibrate the extrinsic parameters based on LiDAR-mapping space occupancy while removing motion distortion. In the final stage, the z-axis errors caused by the plane motion of the autonomous vehicle are corrected, and an accurate extrinsic parameter is finally obtained. Specifically, This method utilizes the planar features in the environment, making it possible to quickly carry out calibration. Experimental results on real-world data sets demonstrate the reliability and accuracy of our method. The codes are open-sourced on the Github website. The code link is https://github.com/OpenCalib/LiDAR2INS.
