4 papers
LM-X: Explainable Vision--Language--Action Modeling via Progress, Event, and Uncertainty Prediction
Jin Lou, Zhiyuan Jing, Xupeng Wang +21
Large-scale vision--language--action (VLA) policies have advanced generalist robot control, yet most remain stimulus-to-action black boxes: actions are exposed, but their explanato…
RoboCousin: Build Your Own Simulation Playground for Robust Bimanual Robotic Manipulation
Jingxuan Zhu, Jingyi Li, LiangLiang Chen +3
Bimanual manipulation policies require large and diverse training datasets, yet collecting demonstrations on physical robots is expensive and difficult to scale. Simulation can gen…
ExACT: An End-to-End Autonomous Excavator System Using Action Chunking With Transformers
Liangliang Chen, Shiyu Jin, Haoyu Wang +1
Excavators are crucial for diverse tasks such as construction and mining, while autonomous excavator systems enhance safety and efficiency, address labor shortages, and improve hum…
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models
Liangliang Chen, Yutian Lei, Shiyu Jin +2
Reinforcement learning (RL) has demonstrated its capability in solving various tasks but is notorious for its low sample efficiency. In this paper, we propose RLingua, a framework…