Bayesian Mutual Theory of Mind


Mutual adaptation between humans and robots


Avoiding Chatters with Hesitation in Human-Robot Co-Learning

Proposed rigorous modeling and analysis of co-learning between humans and robots from a control perspective. Analyzed quantitatively the properties of chatter, and proposed a chatter-avoiding algorithm inspired by the hesitation phenomenon that has been commonly observed in human-human negotiation.


Hybrid Co-Learning for Proximate Human-Robot Teaming

Investigated a hybrid co-learning problem arising from collaborative assembly scenarios, where the robot’s action is operated in the continuous space and the human’s intention transits in the discrete space.