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arXiv · 2610.05011

FreeLoc: Online Floorplan Localization via Diffusion-Aided Pose Refinement

Haocheng Peng·Boyang Zhou·Jiarui Hu·Xiyue Guo·Ziyang Zhang·Boming Zhao·Yifan Gao·Xiao Li·Hujun Bao·Zhaopeng Cui
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Abstract

Floorplans provide compact and widely available geometric maps for indoor localization, but existing high-performing floorplan-based methods still convert them into dense scene-specific offline databases, tying accuracy, storage, and runtime to the sampling resolution of the discretized pose space. We present FreeLoc, an online RGB-based floorplan localization framework that treats the floorplan as a directly queryable geometric map. FreeLoc introduces an efficient online geometric querying and diffusion-aided refinement scheme, which retrieves plausible pose anchors through on-the-fly floorplan ray querying and refines them into accurate continuous pose estimates. For sequential localization, FreeLoc develops an online likelihood construction strategy that bridges single-frame localization and probabilistic temporal fusion by constructing likelihoods from coarse-sampled candidates and refined pose hypotheses, enabling histogram-filter-based temporal fusion without offline databases. Experiments demonstrate real-time online inference and state-of-the-art performance in both single-frame and sequential localization, while real-world results validate practical deployability in indoor robotic localization scenarios.

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Haocheng Peng, Boyang Zhou, Jiarui Hu, Xiyue Guo, Ziyang Zhang, Boming Zhao, Yifan Gao, Xiao Li, Hujun Bao, Zhaopeng Cui. 2026-10-04. FreeLoc: Online Floorplan Localization via Diffusion-Aided Pose Refinement. https://arxiv.org/abs/2610.05011

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