Dynamic Cloth Manipulation with Deep Reinforcement Learning
Rishabh Jangir,Guillem Alenyà,Carme Torras,Rishabh Jangir,Guillem Alenyà,Carme Torras
In this paper we present a Deep Reinforcement Learning approach to solve dynamic cloth manipulation tasks. Differing from the case of rigid objects, we stress that the followed trajectory (including speed and acceleration) has a decisive influence on the final state of cloth, which can greatly vary even if the positions reached by the grasped points are the same. We explore how goal positions for ...
