AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers
Yongchao Chen,Jacob Arkin,Charles Dawson,Yang Zhang,Nicholas Roy,Chuchu Fan,Yongchao Chen,Jacob Arkin,Charles Dawson,Yang Zhang,Nicholas Roy,Chuchu Fan
For effective human-robot interaction, robots need to understand, plan, and execute complex, long-horizon tasks described by natural language. Recent advances in large language models (LLMs) have shown promise for translating natural language into robot action sequences for complex tasks. However, existing approaches either translate the natural language directly into robot trajectories or factor ...
