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arXiv · 2410.04419

LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation

Jianhao Jiao·Jinhao He·Changkun Liu·Sebastian Aegidius·Xiangcheng Hu·Tristan Braud·Dimitrios Kanoulas
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Abstract

This paper presents LiteVLoc, a hierarchical visual localization framework that uses a lightweight topo-metric map to represent the environment. The method consists of three sequential modules that estimate camera poses in a coarse-to-fine manner. Unlike mainstream approaches relying on detailed 3D representations, LiteVLoc reduces storage overhead by leveraging learning-based feature matching and geometric solvers for metric pose estimation. A novel dataset for the map-free relocalization task is also introduced. Extensive experiments including localization and navigation in both simulated and real-world scenarios have validate the system's performance and demonstrated its precision and efficiency for large-scale deployment. Code and data will be made publicly available.

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Jianhao Jiao, Jinhao He, Changkun Liu, Sebastian Aegidius, Xiangcheng Hu, Tristan Braud, Dimitrios Kanoulas. 2024-10-06. LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation. https://arxiv.org/abs/2410.04419

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