PLAN-SEQ-LEARN: A Machine Learning Method that Integrates the Long-Horizon Reasoning Capabilities of Language Models with the Dexterity of Learned Reinforcement Learning RL Policies

The robotics research field has significantly transformed by integrating large language models (LLMs). These advancements have presented an opportunity to guide robotic systems in solving complex tasks that involve intricate planning and long-horizon manipulation. While robots have traditionally relied on predefined skills and specialized engineering, recent developments show potential in using LLMs to help guide […]

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