Robot Learning and LLM-Based Action Planning

2024年1月1日 · 1 min read
research

Research on autonomous action planning and motion generation for robots using imitation learning, reinforcement learning, and Large Language Models (LLMs). We develop state-of-the-art methods including multi-robot task planning combining LLMs and linear programming (LiP-LLM), affordance-centric diffusion policies (TARAD), and humanoid locomotion (LocoGPT).

Robot Learning Large Language Models Imitation Learning Reinforcement Learning
Takato Horii
Authors
Takato Horii (he/him)
Associate Professor
Associate Professor at Graduate School of Engineering Science, Osaka University. Research interests include cognitive developmental robotics, computational modeling of emotional development, and human-robot interaction.