4 papers
MoCaP: Mobile Code-as-Policies for Zero-Shot Mobile Manipulation from Passive Human Videos
Yiyang Cai, Tatsuya Kamijo, Ninghao Lu +2
Passive human videos of everyday activity offer robots access to a massive amount of human experience without requiring a demonstration for each task. However, using this experienc…
World-Gymnast: Training Robots with Reinforcement Learning in a World Model
Ansh Kumar Sharma, Yixiang Sun, Ninghao Lu +3
Robot learning from interacting with the physical world is fundamentally bottlenecked by the cost of physical interaction. The two alternatives, supervised finetuning (SFT) from ex…
Reinforcement Learning for Volt-Var Control: A Novel Two-stage Progressive Training Strategy
Si Zhang, Mingzhi Zhang, Rongxing Hu +3
This paper develops a reinforcement learning (RL)approach to solve a cooperative, multi-agent Volt-Var Control (VVC) problem for high solar penetration distribution systems. The in…
ACDER: Augmented Curiosity-Driven Experience Replay
Boyao Li, Tao Lu, Jiayi Li +3
Exploration in environments with sparse feedback remains a challenging research problem in reinforcement learning (RL). When the RL agent explores the environment randomly, it resu…