Key points are not available for this paper at this time.
Environment perception is a key component of any autonomous system and is often based on a heterogeneous set of sensors and fusion thereof, for which extrinsic sensor calibration plays fundamental role. In this paper, we tackle the problem of 3D LiDAR-radar calibration which is challenging due to low accuracy and sparse informativeness of the radar measurements. We propose a complementary calibration target design suitable for both sensors, thus enabling a simple, yet reliable calibration procedure. The calibration method is composed of correspondence registration and a two-step optimization. The first step, reprojection error based optimization, provides initial estimate of the calibration parameters, while the second step, field of view optimization, uses additional information from the radar cross section measurements and the nominal field of view to refine the parameters. In the end, results of the experiments validated the proposed method and demonstrated how the two steps combined provide an improved estimate of extrinsic calibration parameters.
Peršić et al. (Fri,) studied this question.