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Panoramic Direct LiDAR-assisted Visual Odometry

Authors :
Yuan, Zikang
Xu, Tianle
Wang, Xiaoxiang
Geng, Jinni
Yang, Xin
Source :
in submission 2024
Publication Year :
2024

Abstract

Enhancing visual odometry by exploiting sparse depth measurements from LiDAR is a promising solution for improving tracking accuracy of an odometry. Most existing works utilize a monocular pinhole camera, yet could suffer from poor robustness due to less available information from limited field-of-view (FOV). This paper proposes a panoramic direct LiDAR-assisted visual odometry, which fully associates the 360-degree FOV LiDAR points with the 360-degree FOV panoramic image datas. 360-degree FOV panoramic images can provide more available information, which can compensate inaccurate pose estimation caused by insufficient texture or motion blur from a single view. In addition to constraints between a specific view at different times, constraints can also be built between different views at the same moment. Experimental results on public datasets demonstrate the benefit of large FOV of our panoramic direct LiDAR-assisted visual odometry to state-of-the-art approaches.<br />Comment: 6 pages, 6 figures

Subjects

Subjects :
Computer Science - Robotics
C.5

Details

Database :
arXiv
Journal :
in submission 2024
Publication Type :
Report
Accession number :
edsarx.2409.09287
Document Type :
Working Paper