Enhanced Monocular Visual Odometry with AR Poses and Integrated INS-GPS for Robust Localization in Urban Environments
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916493882556416 |
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| author | Shaw, Ankit |
| author_facet | Shaw, Ankit |
| contents | This paper introduces a cost effective localization system combining monocular visual odometry , augmented reality (AR) poses, and integrated INS-GPS data. We address monocular VO scale factor issues using AR poses and enhance accuracy with INS and GPS data, filtered through an Extended Kalman Filter . Our approach, tested using manually annotated trajectories from Google Street View, achieves an RMSE of 1.529 meters over a 1 km track. Future work will focus on real-time mobile implementation and further integration of visual-inertial odometry for robust localization. This method offers lane-level accuracy with minimal hardware, making advanced navigation more accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_08231 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhanced Monocular Visual Odometry with AR Poses and Integrated INS-GPS for Robust Localization in Urban Environments Shaw, Ankit Robotics This paper introduces a cost effective localization system combining monocular visual odometry , augmented reality (AR) poses, and integrated INS-GPS data. We address monocular VO scale factor issues using AR poses and enhance accuracy with INS and GPS data, filtered through an Extended Kalman Filter . Our approach, tested using manually annotated trajectories from Google Street View, achieves an RMSE of 1.529 meters over a 1 km track. Future work will focus on real-time mobile implementation and further integration of visual-inertial odometry for robust localization. This method offers lane-level accuracy with minimal hardware, making advanced navigation more accessible. |
| title | Enhanced Monocular Visual Odometry with AR Poses and Integrated INS-GPS for Robust Localization in Urban Environments |
| topic | Robotics |
| url | https://arxiv.org/abs/2411.08231 |