Automatic Targetless Extrinsic Calibration of Multiple 3D LiDARs and Radars

Many self-driving vehicles use a multi-sensor system comprising multiple 3D LiDAR and radar sensors for robust all-round perception. Precise calibration of this multi-sensor system is a critical prerequisite for accurate perception data which facilitates safe operation of self-driving vehicles in highly dynamic urban environments. This paper proposes the first-known automatic targetless method for extrinsic calibration of multiple 3D LiDAR and radar sensors, and which only requires the vehicle to be driven over a short distance. The proposed method first estimates the 6-DoF pose of each LiDAR sensor with respect to the vehicle reference frame by minimizing point-to-plane distances between scans from different LiDAR sensors. In turn, a 3D map of the environment is built using data from all calibrated LiDAR sensors on the vehicle. We find the 6-DoF pose of each radar sensor with respect to the vehicle reference frame by minimizing (1) point-to-plane distances between radar scans and the 3D map, and (2) radial velocity errors. Our proposed calibration method does not require overlapping fields of view between LiDAR and radar sensors. Real-world experiments demonstrate the accuracy and repeatability of the proposed calibration method.