TC-VIML
Xi Zheng
November 11, 2025
Tightly-coupled Visual/Inertial/Map integration with observability analysis for reliable localization of intelligent vehicles.
TC-VIML proposes a tightly-coupled visual-inertial odometry (VIO) system that leverages a 3D prior line map for drift-free localization. Unlike loosely-coupled methods, our approach deeply integrates line features into a factor graph optimization framework, supported by a robust cross-modality matching and outlier rejection strategy.
Key Contributions:
- Tight integration of 2D image line features with a 3D prior line map via factor graph optimization
- Robust cross-modality matching and outlier rejection for line feature association
- First rigorous proof that the system achieves full observability in global translation (only yaw unobservable)
- Validated in both simulated and real-world urban driving environments
Citation:
@article{zheng2024tightly,
title={Tightly-coupled visual/inertial/map integration with observability analysis for reliable localization of intelligent vehicles},
author={Zheng, Xi and Wen, Weisong and Hsu, Li-Ta},
journal={IEEE Transactions on Intelligent Vehicles},
year={2024},
publisher={IEEE}
}
@inproceedings{zheng2023tightly,
title={Tightly-coupled line feature-aided visual inertial localization within lightweight 3D prior map for intelligent vehicles},
author={Zheng, Xi and Wen, Weisong and Hsu, Li-Ta},
booktitle={IEEE ITSC},
pages={6019--6026},
year={2023}
}