OpenNavMap: Structure-Free Topometric Mapping via Large-Scale Collaborative Localization
Jianhao Jiao, Changkun Liu, Jingwen Yu, Boyi Liu, Qianyi Zhang, Yue Wang, Dimitrios Kanoulas

TL;DR
OpenNavMap introduces a scalable, structure-free topometric mapping system that leverages large-scale geometric models for robust, efficient multi-session localization and navigation without pre-built 3D models.
Contribution
It presents a novel lightweight, structure-free approach for large-scale collaborative localization using geometric foundation models, improving accuracy and robustness over traditional methods.
Findings
Achieves 0.62m average translation error on benchmark
Maintains global consistency over 15km multi-session data
Successfully completes 12 autonomous navigation tasks
Abstract
Scalable and maintainable map representations are fundamental to enabling large-scale visual navigation and facilitating the deployment of robots in real-world environments. While collaborative localization across multi-session mapping enhances efficiency, traditional structure-based methods struggle with high maintenance costs and fail in feature-less environments or under significant viewpoint changes typical of crowd-sourced data. To address this, we propose OPENNAVMAP, a lightweight, structure-free topometric system leveraging 3D geometric foundation models for on-demand reconstruction. Our method unifies dynamic programming-based sequence matching, geometric verification, and confidence-calibrated optimization to robust, coarse-to-fine submap alignment without requiring pre-built 3D models. Evaluations on the Map-Free benchmark demonstrate superior accuracy over…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotics and Sensor-Based Localization · Advanced Vision and Imaging · Advanced Image and Video Retrieval Techniques
