My research goal is to enable complex robotic systems to learn complex tasks. Thus, I am interested in developing a scalable robot learning framework that can leverage prior knowledge and diverse data.
Particularly, as the first milestone, I focus on solving a long-horizon manipulation task, Furniture Assembly, which requires many aspects of intelligent robots from structural reasoning to long-term planning to sophisticated control.
|Long-horizon task benchmark||IKEA Environment (2019)|
|Skill composition||Transition-RL (2019), Skill-Coordination (2020), T-STAR (2021)|
|Learning with skills and skill prior||SPiRL (2020), SkiLD (2021), SkiMo (2022)|
|Imitation learning||SILO (2019), Goal Proximity IL (2021)|
|Safe exploration||MoPA-RL (2020)|
|Simulation-to-real||IDAPT (2021), MoPA-PD (2021)|