LAUSR

LiDARs and cameras are two widely used sensors in robotics and computer vision, particularly for navigation and recognition in 3D scenarios. Systems combining both may benefit from the precise depth of the former and the high-density information of the latter, but a calibration process is necessary to relate them spatially. In this paper, we introduce COUPLED, a method that finds the extrinsic parameters to relate information between them. The method implies the use of a setup consisting of three planes with charuco patterns to find the planes in both systems. We obtain corresponding points in both systems through geometric relations between the planes. Afterward, we use these points and the Kabsch algorithm to compute the transformation that merges the planes between both systems. Compared to recent single plane algorithms, we obtain more accurate parameters, and only one pose is required. In the process, we develop a method to automatically find the calibration target using a plane detector instead of manually selecting the target in the LiDAR frame.