AIBullisharXiv – CS AI · Mar 57/10
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Large-Language-Model-Guided State Estimation for Partially Observable Task and Motion Planning
Researchers developed CoCo-TAMP, a robot planning framework that uses large language models to improve state estimation in partially observable environments. The system leverages LLMs' common-sense reasoning to predict object locations and co-locations, achieving 62-73% reduction in planning time compared to baseline methods.