1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Back to the Manifold: Recovering from Out-of-Distribution States
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin +2
Learning from previously collected datasets of expert data offers the promise of acquiring robotic policies without unsafe and costly online explorations. However, a major challeng…
cs.RO2016
A Sensorimotor Reinforcement Learning Framework for Physical Human-Robot Interaction
Ali Ghadirzadeh, Judith Bütepage, Atsuto Maki +2
Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-effici…