Abstract
The present study focuses on the simultaneous localization and mapping (SLAM) system based on point and line features. Aiming to address the prevalent issue of repeated detection during line feature extraction in low-texture environments, a novel method for merging redundant line features is proposed. This method effectively mitigates the problem of increased initial pose estimation error that arises when the same line is erroneously detected as multiple lines in adjacent frames. Furthermore, recognizing the potential for the introduction of line features to prolong the marginalization process of the information matrix, optimization strategies are employed to accelerate this process. Additionally, to tackle the issue of insufficient point feature accuracy, subpixel technology is introduced to enhance the precision of point features, thereby further reducing errors. Experimental results on the European Robotics Challenge (EUROC) public dataset demonstrate that the proposed LR-SLAM system exhibits significant advantages over mainstream SLAM systems such as ORB-SLAM3, VINS-Mono, and PL-VIO in terms of accuracy, efficiency, and robustness.
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The authors would like to thank the editors and anonymous reviewers for their time and effort in evaluating this paper and for the constructive comments for the improvement of its presentation and quality.
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This paper is partly supported by the National Science and Technology Major Project (2022ZD0119900), National Natural Science Foundation of China (U2141234 and 62463004), Shanghai Science and Technology program (22015810300), Hainan Province Science and Technology Special Fund (ZDYF2024GXJS003), and Scientific Research Fund of Hainan University (KYQD(ZR)23025).
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Conceptualization, JH, CNM, LY, GDS, ZWD; methodology, JH; software and validation, CNM; writing original draft preparation JH and LY; writing review and editing GDS and ZWD; supervision GDS; project administration ZWD; All authors have read and agreed to the published version of the manuscript.
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Jiang, H., Cang, N., Lin, Y. et al. LR-SLAM: Visual Inertial SLAM System with Redundant Line Feature Elimination. J Intell Robot Syst 110, 169 (2024). https://doi.org/10.1007/s10846-024-02184-2
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DOI: https://doi.org/10.1007/s10846-024-02184-2