Generating Executable Action Plans with Environmentally-Aware Language Models
Maitrey Gramopadhye,Daniel Szafir,Maitrey Gramopadhye,Daniel Szafir
Large Language Models (LLMs) trained using massive text datasets have recently shown promise in generating action plans for robotic agents from high-level text queries. However, these models typically do not consider the robot's environment, resulting in generated plans that may not actually be executable, due to ambiguities in the planned actions or environmental constraints. In this paper, we pr...
