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arXiv · 2406.00312

NuRF: Nudging the Particle Filter in Radiance Fields for Robot Visual Localization

Wugang Meng·Tianfu Wu·Huan Yin·Fumin Zhang
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Abstract

Can we localize a robot on a map only using monocular vision? This study presents NuRF, an adaptive and nudged particle filter framework in radiance fields for 6-DoF robot visual localization. NuRF leverages recent advancements in radiance fields and visual place recognition. Conventional visual place recognition meets the challenges of data sparsity and artifact-induced inaccuracies. By utilizing radiance field-generated novel views, NuRF enhances visual localization performance and combines coarse global localization with the fine-grained pose tracking of a particle filter, ensuring continuous and precise localization. Experimentally, our method converges 7 times faster than existing Monte Carlo-based methods and achieves localization accuracy within 1 meter, offering an efficient and resilient solution for indoor visual localization.

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Wugang Meng, Tianfu Wu, Huan Yin, Fumin Zhang. 2024-06-01. NuRF: Nudging the Particle Filter in Radiance Fields for Robot Visual Localization. https://arxiv.org/abs/2406.00312

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