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arXiv · 2502.20386

ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting

Dexter Ong·Yuezhan Tao·Varun Murali·Igor Spasojevic·Vijay Kumar·Pratik Chaudhari
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Abstract

We address the challenge of task-oriented navigation in unstructured and unknown environments, where robots must incrementally build and reason on rich, metric-semantic maps in real time. Since tasks may require clarification or re-specification, it is necessary for the information in the map to be rich enough to enable generalization across a wide range of tasks. To effectively execute tasks specified in natural language, we propose a hierarchical representation built on language-embedded Gaussian splatting that enables both sparse semantic planning that lends itself to online operation and dense geometric representation for collision-free navigation. We validate the effectiveness of our method through real-world robot experiments conducted in both cluttered indoor and kilometer-scale outdoor environments, with a competitive ratio of about 60% against privileged baselines. Experiment videos and more details can be found on our project page: https://atlasnav.github.io

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Dexter Ong, Yuezhan Tao, Varun Murali, Igor Spasojevic, Vijay Kumar, Pratik Chaudhari. 2025-02-27. ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting. https://arxiv.org/abs/2502.20386

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