Automatic Calibration of Multiple 3D LiDARs in Urban Environments Multiple LiDARs have progressively emerged on autonomous vehicles for rendering a rich view and dense measurements. However, the lack of precise calibration negatively affects their potential applications. In this paper, we propose a novel system that enables automatic multiLiDAR calibration method without any calibration target, prior environment information, and manual initialization. Our approach starts with a handeye calibration by aligning the motion of each sensor. The initial results are then refined by an appearancebased method by minimizing a cost function constructed by pointplane distance. Experimental results on simulated and realworld data demonstrate the reliability and accuracy of our calibration approach. The proposed approach can calibrate a multiLiDAR system with the rotation and translation errors less than 0. 04rad and 0. 1m respectively for a mobile platform.

A Novel DualLidar Calibration Algorithm Using Planar Surfaces. Multiple lidars are prevalently used on mobile vehicles for rendering a broad view to enhance the performance of localization and perception systems. However, precise calibration of multiple lidars is challenging since the feature correspondences in scan points cannot always provide enough constraints. To address this problem, the existing methods require fixed calibration targets in scenes or rely exclusively on additional sensors. In this paper, we present a novel method that enables automatic lidar calibration without these restrictions. Three linearly independent planar surfaces appearing in surroundings is utilized to find correspondences. Two components are developed to ensure the extrinsic parameters to be found: a closedform solver for initialization and an optimizer for refinement by minimizing a nonlinear cost function. Simulation and experimental results demonstrate the high accuracy of our calibration approach with the rotation and translation errors smaller than 0.05rad and 0.1m respectively.