  In this letter, we present a novel method for automatic extrinsic calibration
of high-resolution LiDARs and RGB cameras in targetless environments. Our
approach does not require checkerboards but can achieve pixel-level accuracy by
aligning natural edge features in the two sensors. On the theory level, we
analyze the constraints imposed by edge features and the sensitivity of
calibration accuracy with respect to edge distribution in the scene. On the
implementation level, we carefully investigate the physical measuring
principles of LiDARs and propose an efficient and accurate LiDAR edge
extraction method based on point cloud voxel cutting and plane fitting. Due to
the edges' richness in natural scenes, we have carried out experiments in many
indoor and outdoor scenes. The results show that this method has high
robustness, accuracy, and consistency. It can promote the research and
application of the fusion between LiDAR and camera. We have open-sourced our
code on GitHub to benefit the community.
