A4LidarTag: Depth-Based Fiducial Marker for Extrinsic Calibration of Solid-State Lidar and Camera
Yusen Xie, Lei Deng, Ting Sun, Yeyu Fu, Jian Li, Xinglong Cui, Hanxi Yin, Shuixin Deng
Abstract
Visual-based simultaneous localization and mapping (SLAM) systems perform weakly in object tracking and map reconstruction due to the unreliable depth measurement originating from image-only data. Light Detection and Ranging (LiDAR) can be coupled to overcome the drawback of uncertain depth estimation. The prerequisite for performing data fusion is to align visual-Lidar sensors to a specific coordinate system with extrinsic pose by calibrating. The conventional extrinsic calibration frameworks either rely on markers in artificial large-size calibration boards or uncontrollable natural scenes (Fig. 2 ), limiting stability and convenience. In this paper, we have designed a novel marker pattern, A4LidarTag, composed of circular holes. The difference in depth measurement is used to encode location information. Based on A4LidarTag, the automatic extrinsic calibration framework between solid-state Lidar (SSL) and the camera is developed. The proposed framework can be implemented in close range (within 1 m) and on an A4-size calibration board. The average reprojection error resulting from Lidar point clouds projection is about 0.12pixels. Experiments show excellent efficiency and versatility in both indoor and outdoor scenes.
BibTeX
@inproceedings{ral2022_a4lidartagdepthb,
title = {A4LidarTag: Depth-Based Fiducial Marker for Extrinsic Calibration of Solid-State Lidar and Camera},
author = {Yusen Xie and Lei Deng and Ting Sun and Yeyu Fu and Jian Li and Xinglong Cui and Hanxi Yin and Shuixin Deng and Junwei Xiao and Baohua Chen},
booktitle = {RA-L 2022},
year = {2022}
}