This paper presents a method for the extrinsic calibration of a 3D light detection and ranging (LiDAR) sensor with respect to a camera with point constraints. While its methodology is an extension of the previously proposed 2D LiDAR calibration method, a novel approach to obtaining point constraints is proposed, where a simple point target and a mechanical linear-actuator are utilized to precisely and efficiently obtain point-to-point correspondences in the image and LiDAR frames. Its calibration performance is then examined in terms of not only parameter estimation but also reprojection. Consequently, it is observed that the estimation and reprojection results of the proposed method with point constraints are better than those of a well-used baseline method with plane constraints.

This letter provides a simulation study on calibration of a 3D LiDAR with respect to a camera, with point-topoint and point-on-plane correspondences for calibration constraints, by extending our previously proposed 2D LiDAR calibration methods. The calibration performance is examined in terms of vertical scan view and resolution, especially in narrow/sparse scan space, in the presence of sensor noise. It contributes to a guidance on a use of various sensors and dataset depending on contexts and applications with different scan view and resolution, and an understanding of the effect of the different constraints on calibration. As a result, the combination of the point and plane constraints yields better performance than either of them.