papers AI Learner
The Github is limit! Click to go to the new site.

Automatic Calibration of Multiple 3D LiDARs in Urban Environments

2019-05-13
Jianhao Jiao, Yang Yu, Qinghai Liao, Haoyang Ye, Ming Liu

Abstract

Multiple LiDARs have progressively emerged on autonomous vehicles for rendering a wide field of view and dense measurements. However, the lack of precise calibration negatively affects their potential applications in localization and perception systems. In this paper, we propose a novel system that enables automatic multi-LiDAR calibration without any calibration target, prior environmental information, and initial values of the extrinsic parameters. Our approach starts with a hand-eye calibration for automatic initialization by aligning the estimated motions of each sensor. The resulting parameters are then refined with an appearance-based method by minimizing a cost function constructed from point-plane correspondences. Experimental results on simulated and real-world data sets demonstrate the reliability and accuracy of our calibration approach. The proposed approach can calibrate a multi-LiDAR system with the rotation and translation errors less than 0.04 [rad] and 0.1 [m] respectively for a mobile platform.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1905.04912

PDF

http://arxiv.org/pdf/1905.04912


Similar Posts

Comments