A Sparse Topometric Graph for Scalable Cross-Session Indoor Navigation
A conventional embodied agent in an indoor environment builds a map by accumulating noisy real-world measurements and results from heavy inference to guide navigation. While the detailed measurements may differ due to scene changes or sensor settings, the unique topological structure of navigable passages or the connectivity between rooms may provide training-free guidance that complements local observations. We propose a sparse topometric graph as an efficient structural representation for robust indoor navigation, alleviating the need for fine-grained matching, which is computationally expensive, memory-intensive, and prone to real-world variations. The map consists of nodes that encode...
| Authors | Eun Sun Lee, Minkyun Seo, Gwangtak Bae et al. |
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| Primary category | cs.RO |
| Published | 22 October 2026 |
| Last updated at source | 22 October 2026 |
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