Extrinsic calibration of a 3D LIDAR and a camera using a trihedron

In this paper, we propose a novel method to easily conduct the extrinsic calibration between a camera and a 3D LIDAR. By taking advantage of orthogonal trihedrons which are ubiquitous in structured environments, our method makes it convenient for a mobile robot to collect the data needed for calibration. The proposed method estimates the relative position of the sensors by first determining the pose of each plane of the trihedron in two acquisitions and then solving a planarity-constrained optimization problem. The algorithm is validated first by performing experiments on simulated data and investigating its sensitivity to noise. Moreover, we carry out a calibration for a real 3D LIDAR–camera system and further apply the calibration results to render 3D points with pixels' colors. The colored 3D points visually validate the effectiveness of our method.

► We propose a new method for the extrinsic calibration of a system consisting of a 3D LIDAR and a camera.
► Our method takes advantage of a orthogonal trihedron, which is ubiquitous in structured environments, as the calibration rig.
► Our method is convenient to conduct the extrinsic calibration and gets good results.
► The calibration results obtained by our method can be further used for sensor fusion.