Automatic Extrinsic Calibration of a Camera and a 2D LiDAR With Point-Line Correspondences

Extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to fuse information from two sensors by representing the information under the same frame. Various geometric constraints such as point-plane, point-line, and point-point are used for the extrinsic calibration. Usually, these require a manual step, including control points selection for camera calibration and LiDAR points. We propose a new algorithm for automatic extrinsic calibration with point-line correspondences. A calibration structure with two perpendicular planes having a chessboard on both sides is used for the extrinsic calibration. First, we use predefined colors at specific locations on a chessboard to quickly find the origin of the coordinate system. Second, we robustly detect three control points on LiDAR raw data using a geometric constraint that two end points among three control points should lie on the same line. The initial linear solution is obtained by using a point-line constraint. Finally, it is refined by nonlinear minimization, which gives a 15.3% improvement compared to the linear solution. Experimental results show the feasibility of the proposed algorithm.

Automated summary

The extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to integrate information from both sensors in the same coordinate system. Various geometric constraints, such as point-plane, point-line, and point-point constraints, are used for the extrinsic calibration. This study proposes a new algorithm for automatic extrinsic calibration using point-line correspondences. Experimental results demonstrate the feasibility of the proposed algorithm, showing a 15.3% improvement compared to the linear solution after nonlinear minimization.