Model-driven reinforcement learning and action dimension extension method for efficient asymmetric assembly
Yuhang Gai,Jiuming Guo,Dan Wu,Ken Chen,Yuhang Gai,Jiuming Guo,Dan Wu,Ken Chen
Complex assembly tasks remain huge challenge for robots because the traditional control methods rely on complicated contact state analysis. Reinforcement learning (RL) becomes one of the preferred embodiments to construct the control strategy of complex tasks. In this paper, the method of model-driven RL (MDRL) is employed to construct the control strategy. Then a completely innovative action dime...
