Chapter 10: Learning industrial assembly by guided-DDPG
Yongxiang Fan FANUC Advanced Research Laboratory, FANUC America Corporation, Union City, CA, United States
Abstract
Assembly skills are essential for industrial manipulators to achieve automatic assembly and to realize full automation. Traditional assembly tasks use predefined trajectories or tuned force control parameters, which make the automatic assembly time consuming, difficult to generalize, and not robust to uncertainties. We propose a learning framework for industrial assembly. The framework combines both supervised learning and reinforcement learning. Supervised learning utilizes trajectory optimization to provide the initial guidance to the policy, while reinforcement learning ...
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