Abstract
Planarity of checkerboards is a widely used feature for extrinsic calibration of camera and LiDAR. In this study, we propose two analytically derived covariances of (i) plane parameters and (ii) plane measurement, for precise extrinsic calibration of camera and LiDAR. These covariances allow the graded approach in planar feature correspondences by exploiting the uncertainty of a set of given features in calibration. To construct plane parameter covariance, we employ the error model of 3D corner points and the analytically formulated plane parameter errors. Next, plane measurement covariance is directly derived from planar regions of point clouds using the out-of-plane errors. In simulation validation, our method is compared to an existing uncertainty-excluding method using the different number of target poses and the different levels of noise. In field experiment, we validated the applicability of the proposed analytic plane covariances for precise calibration using the basic planarity-based method and the latest planarity-and-linearity-based method.
Original language | English |
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Title of host publication | 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 6042-6048 |
Number of pages | 7 |
ISBN (Electronic) | 9781728173955 |
DOIs | |
Publication status | Published - 2020 May |
Event | 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France Duration: 2020 May 31 → 2020 Aug 31 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
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ISSN (Print) | 1050-4729 |
Conference
Conference | 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 |
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Country/Territory | France |
City | Paris |
Period | 20/5/31 → 20/8/31 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This research was supported by the Brain Korea 21 Plus project in 2020, and the grant (20NSIP-B135746-04) from National Spatial Information Research Program (NSIP) funded by Ministry of Land, Infrastructure and Transport of Korean government.
Publisher Copyright:
© 2020 IEEE.
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering