Mingxin Tan

CORE: Common Outcome Regularities from Action-Free Visual Demonstrations for Robot Manipulation

Juyi Sheng, Jincheng Li, Mingxin Tan, Mengyuan Liu

Robot imitation learning often relies on costly robot demonstrations, while abundant action-free visual demonstrations, such as human videos, are difficult to use because they lack robot-executable actions and suffer from embodiment gaps. We propose CORE, a policy learning framew…Read more