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NLMap-SayCan
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Project page for Open-vocabulary Queryable Scene Representations for Real World Planning
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author
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2026-03-05 10:58:44
raw text
NLMap-SayCan Open-vocabulary Queryable Scene Representations for Real World Planning Boyuan Chen Fei Xia Brian Ichter Kanishka Rao Keerthana Gopalakrishnan Michael S. Ryoo Austin Stone Daniel Kappler Everyday Robots Robotics at Google Paper Video Abstract Large language models (LLMs) have unlocked new capabilities of task planning from human instructions. However, prior attempts to apply LLMs to real-world robotic tasks are limited by the lack of grounding in the surrounding scene. In this paper, we develop NLMap, an open-vocabulary and queryable scene representation to address this problem. NLMap serves as a framework to gather and integrate contextual information into LLM planners, allowing them to see and query available objects in the scene before generating a context-conditioned plan. NLMap first establishes a natural...
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