A SLAM Method Based on ORB-SLAM3 Which Mixed GNSS Data
Pages 398 - 403
Abstract
Traditional single-sensor SLAM methods suffer from cumulative drift errors in large-scale outdoor environments, which makes it difficult to have good localization accuracy in practical application scenarios. In this paper, to solve the above problems, we propose a visual inertial system fusion method with global navigation satellite system (GNSS), which transforms GNSS measurements into values in Cartesian coordinate system, and then uses odometry pose information and GNSS information to do nonlinear optimization to eliminate the cumulative drift error within the system, and experiments are carried out on the KITTI raw data, which show that the method proposed in this paper effectively improves the localization accuracy in large-scale outdoor environments. The results show that the method proposed in this paper effectively improves the localization accuracy in outdoor large-scale scenarios, and the localization accuracy on the KITTI dataset is 54% higher than that of ORB-SLAM3 on average.
References
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Campos C, Elvira R, Rodríguez J J G, Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam[J]. IEEE Transactions on Robotics, 2021, 37(6): 1874-1890.
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Published In
November 2023
764 pages
ISBN:9798400708299
DOI:10.1145/3640115
Copyright © 2023 ACM.
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Publication History
Published: 26 March 2024
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ICITEE 2023
ICITEE 2023: 6th International Conference on Information Technologies and Electrical Engineering
November 3 - 5, 2023
Changde, Hunan, China
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