A Novel Extrinsic Calibration Method of Mobile Manipulator Camera and 2D-LiDAR via Arbitrary Trihedron-Based Reconstruction

Mobile manipulators are increasingly applied to improve the efficiency in industrial manufacturing. As a typical system using multi-sensor fusion technology, accurate extrinsic calibration of manipulator's exteroceptive sensors like camera and 2D-LiDAR is essential for mobile manipulators to perform complicated task such as mobile assembly. However, most existing camera-LiDAR calibration methods require sophisticated artificial calibration targets, leading to implementation restrictions. In this paper, by reconstructing an arbitrary trihedron that existed in the general human-made environment, a novel method is presented to estimate the transformation between the manipulator camera and the 2D-LiDAR coordinate system. The proposed method is based on the use of point, line, and plane geometry constraints between the segmented 2D-LiDAR scan and the reconstructed trihedron features. Considering the metric of reconstruction, the extended hand-eye calibration framework is implemented to recover the scale factor and hand-eye parameters. Then, a new optimization model is presented to reconstruct the key features of arbitrary trihedron in a preset global coordinate system. Finally, with only one 2D-LiDAR measurement, camera-LiDAR transformation can be calculated by constructing point-to-line and line-to-plane geometric constraints. Further, the transformation between the manipulator kinematic base and 2D-LiDAR can also be calibrated. Both simulation and real-world experiments show that the proposed method can provide robust and accurate results.