  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.
