Abstract
With Light Detection and Ranging(LiDAR) technology's development and maturity, various new LiDARs have emerged in recent years, such as the Mid-40 series launched by Livox. Compared with the rotating Velodyne LiDAR, its small scanning range and irregular scanning trajectory pose challenges for SLAM applications. We evaluate the characteristics of Mid-40, and propose a calibration method based on checkerboard patterns. Our calibration method extracts the checkerboard corners' coordinates from both the point cloud and the image, which are then used to establish 3D-2D matching constraints. By solving the constraints, we can obtain extrinsic parameters between the LiDAR and camera without the need to label the corner features manually. Experimental results suggested that our method is able to solve the extrinsic calibration problem between Livox Mid-40 LiDAR and the monocular camera with high accuracy.
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