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arXiv · 2410.08262

ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization

Mason B. Peterson·Yixuan Jia·Yulun Tian·Annika Thomas·Jonathan P. How
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Abstract

Global localization is a fundamental capability required for long-term and drift-free robot navigation. However, current methods fail to relocalize when faced with significantly different viewpoints. We present ROMAN (Robust Object Map Alignment Anywhere), a global localization method capable of localizing in challenging and diverse environments by creating and aligning maps of open-set and view-invariant objects. ROMAN formulates and solves a registration problem between object submaps using a unified graph-theoretic global data association approach with a novel incorporation of a gravity direction prior and object shape and semantic similarity. This work's open-set object mapping and information-rich object association algorithm enables global localization, even in instances when maps are created from robots traveling in opposite directions. Through a set of challenging global localization experiments in indoor, urban, and unstructured/forested environments, we demonstrate that ROMAN achieves higher relative pose estimation accuracy than other image-based pose estimation methods or segment-based registration methods. Additionally, we evaluate ROMAN as a loop closure module in large-scale multi-robot SLAM and show a 35% improvement in trajectory estimation error compared to standard SLAM systems using visual features for loop closures. Code and videos can be found at https://acl.mit.edu/roman.

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Mason B. Peterson, Yixuan Jia, Yulun Tian, Annika Thomas, Jonathan P. How. 2024-10-10. ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization. https://arxiv.org/abs/2410.08262

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