@inproceedings{12a52c3c340e4e7f973e4e3995e72212,
title = "An RGB-Thermal-Inertial Odometry with Dual-Track Front-end and Asynchronous Factor Graph Optimization",
abstract = "The localization of unmanned systems in degraded visual environments (DVEs) has emerged as a critical research challenge in recent years. This paper studies the issues of robust multi-modal fusion and sensor degradation for RGB-Thermal-Inertial Odometry frameworks. A dual-track front-end method combining deep-learning descriptors and KLT optical flow is designed, ensuring reliable cross-modal association and efficient temporal tracking. Meanwhile, a scene-aware feature adapter and an asynchronous factor graph are developed to address sensor anomalies through dynamic sensor balancing and seamless monocular-binocular transitions. The effectiveness and superiority of the proposed framework are validated through real-world experiments in lighting transitions and smoke scenarios, significantly outperforming state-of-the-art systems with high localization accuracy at real-time frequencies.",
keywords = "Odometry, State estimator, Thermal, Visual, scene-aware feature adapter",
author = "Pei Wang and Bo Liu and Qinghua Li and Siyuan Wang",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 6th International Symposium on Intelligent Robotics and Systems, ISoIRS 2026 ; Conference date: 27-03-2026 Through 29-03-2026",
year = "2026",
doi = "10.1109/ISOIRS70157.2026.11545274",
language = "英语",
series = "Proceedings of ISoIRS 2026 - Moving Towards Embodied Intelligence in the AI Age: 2026 6th International Symposium on Intelligent Robotics and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of ISoIRS 2026 - Moving Towards Embodied Intelligence in the AI Age",
address = "美国",
}