Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning
Guillermo Garcia-Hernando,Edward Johns,Tae-Kyun Kim,Guillermo Garcia-Hernando,Edward Johns,Tae-Kyun Kim
Dexterous manipulation of objects in virtual environments with our bare hands, by using only a depth sensor and a state-of-the-art 3D hand pose estimator (HPE), is challenging. While virtual environments are ruled by physics, e.g. object weights and surface frictions, the absence of force feedback makes the task challenging, as even slight inaccuracies on finger tips or contact points from HPE may...
