@INPROCEEDINGS{7313228, 
author={G. Xie and T. Xu and C. Isert and M. Aeberhard and S. Li and M. Liu}, 
booktitle={2015 IEEE 18th International Conference on Intelligent Transportation Systems}, 
title={Online Active Calibration for a Multi-LRF System}, 
year={2015}, 
volume={}, 
number={}, 
pages={806-811}, 
abstract={Multi-LRF(Laser Range Finder) systems have been broadly utilized in sensor fusion for automobile. In order to convert multiple LRF data into a unified coordinate system, we have to obtain the rigid transformation among multi-LRF. In this paper, we propose a new algorithm for online extrinsic calibration of multi-LRFs by observing a planar checkerboard pattern and solving for transformation between the views of a planar checkerboard from a camera and multi-LRF. Existing LRF calibration is achieved by freely moving a checkerboard pattern and conducting much offline optimization. Compared with traditional algorithm, the advantages of our approach are twofold. Firstly, adopting the noise of images and LRF depth readings, we can exactly calculate the exact position and pose of the checkerboard that can largely reduce the transformation error. Secondly, the complete calibration process is online, which means the exact position and pose of the checkerboard can be obtained in real-time and manipulated by robotic arm. In the end, our calibration approach is validated through real experiments that show the superiority with respect to the state-of-art methods.}, 
keywords={automobiles;calibration;intelligent transportation systems;laser ranging;optimisation;sensor fusion;automobile;checkerboard pattern;laser range finder system;multiLRF system;offline optimization;online active calibration;sensor fusion;Bismuth;Calibration;Cameras;Monte Carlo methods;Noise;Noise measurement;Optimization}, 
doi={10.1109/ITSC.2015.136}, 
ISSN={2153-0009}, 
month={Sept},}