Journal of System Simulation
Abstract
Abstract: To address unstability of location accuracy of ORB-SLAM system caused by randomness of camera pose solution method, an improved pose solution method based on feature point windowed matching and analytical ICP is proposed, and the mobile robot ORB-SLAM system is constructed. The extracted feature points are windowed to improve matching efficiency while ensuring good feature point matching, the analytical ICP algorithm is used to solve the camera pose for avoiding iteration, and the windowed pose solution with the smallest error is selected for bundle adjustment to reduce the pose errors caused by local information loss or mismatching. The results show that the proposed method could reduce the trajectory error by more than 30% on average compared with ORB-SLAM2 and ORBSLAM3, and can decrease the probability of camera tracking failure.
Recommended Citation
Yao, Wanye; Pang, Zewei; Sun, Peijie; and Wang, Zhu
(2024)
"Research on ORB-SLAM Algorithm Based on Windowed Matching Estimation,"
Journal of System Simulation: Vol. 36:
Iss.
9, Article 5.
DOI: 10.16182/j.issn1004731x.joss.23-052
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss9/5
First Page
2032
Last Page
2042
CLC
TP391.9
Recommended Citation
Yao Wanye, Pang Zewei, Sun Peijie, et al. Research on ORB-SLAM Algorithm Based on Windowed Matching Estimation[J]. Journal of System Simulation, 2024, 36(9): 2032-2042.
DOI
10.16182/j.issn1004731x.joss.23-052
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