Experimental Evaluation of 3D-LIDAR Camera Extrinsic Calibration

In this paper we perform an extensive experimental evaluation of three planar target based 3D-LIDAR camera calibration algorithms, on a sensor suite consisting multiple 3D-LIDARs and cameras, assessing their robustness to random initialization and by using metrics like Mean Line Re-projection Error...

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Bibliographic Details
Published in:	2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 9020 - 9026
Main Authors:	Mishra, Subodh, Osteen, Philip R., Pandey, Gaurav, Saripalli, Srikanth
Format:	Conference Proceeding
Language:	English
Published:	IEEE 24-10-2020
Subjects:	3D-LIDAR Calibration Camera Cameras Extrinsic Calibration Intelligent robots Noise measurement Non-Linear Least Square Production facilities Robot vision systems Robustness
Online Access:	Get full text
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Summary:	In this paper we perform an extensive experimental evaluation of three planar target based 3D-LIDAR camera calibration algorithms, on a sensor suite consisting multiple 3D-LIDARs and cameras, assessing their robustness to random initialization and by using metrics like Mean Line Re-projection Error (MLRE) and Factory Stereo Calibration Error. We briefly describe each method and provide insights into practical aspects like ease of data collection. We also show the effect of noisy sensor on the calibration result and conclude with a note on which calibration algorithm should be used under what circumstances.
ISSN:	2153-0866
DOI:	10.1109/IROS45743.2020.9340911