Discovering Synergies for Robot Manipulation with Multi-Task Reinforcement Learning
Zhanpeng He,Matei Ciocarlie,Zhanpeng He,Matei Ciocarlie
Controlling robotic manipulators with high-dimensional action spaces for dexterous tasks is a challenging problem. Inspired by human manipulation, researchers have studied generating and using postural synergies for robot hands to accomplish manipulation tasks, leveraging the lower dimensional nature of synergistic action spaces. However, many of these works require pre-collected data from an exis...
