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LLM-based Interactive Imitation Learning for Robotic Manipulation
Jonas Werner, Kun Chu, Cornelius Weber +1
Recent advancements in machine learning provide methods to train autonomous agents capable of handling the increasing complexity of sequential decision-making in robotics. Imitatio…
LLM+MAP: Bimanual Robot Task Planning using Large Language Models and Planning Domain Definition Language
Kun Chu, Xufeng Zhao, Cornelius Weber +1
Bimanual robotic manipulation provides significant versatility, but also presents an inherent challenge due to the complexity involved in the spatial and temporal coordination betw…
Large Language Models for Orchestrating Bimanual Robots
Kun Chu, Xufeng Zhao, Cornelius Weber +3
Although there has been rapid progress in endowing robots with the ability to solve complex manipulation tasks, generating control policies for bimanual robots to solve tasks invol…
Accelerating Reinforcement Learning of Robotic Manipulations via Feedback from Large Language Models
Kun Chu, Xufeng Zhao, Cornelius Weber +2
Reinforcement Learning (RL) plays an important role in the robotic manipulation domain since it allows self-learning from trial-and-error interactions with the environment. Still,…