  With the rapid development of autonomous driving and SLAM technology, the
performance of autonomous systems using multimodal sensors highly relies on
accurate extrinsic calibration. Addressing the need for a convenient,
maintenance-friendly calibration process in any natural environment, this paper
introduces Galibr, a fully automatic targetless LiDAR-camera extrinsic
calibration tool designed for ground vehicle platforms in any natural setting.
The method utilizes the ground planes and edge information from both LiDAR and
camera inputs, streamlining the calibration process. It encompasses two main
steps: an initial pose estimation algorithm based on ground planes (GP-init),
and a refinement phase through edge extraction and matching. Our approach
significantly enhances calibration performance, primarily attributed to our
novel initial pose estimation method, as demonstrated in unstructured natural
environments, including on the KITTI dataset and the KAIST quadruped dataset.
