Deep Reinforcement Learning for Facilitating Human-Robot Interaction in Manufacturing

The ability for humans to work in close contact with robots in a manufacturing environment has been limited due to safetySafety in manufacturing concerns and the robot’s inability to sense, react, and coordinate with a human without explicit, rigid programming. However, advances in Deep Reinforcement Learning (DRL) have shown considerable promise in developing processes that allow robots to work in a dynamic environment, solving problems and adapting to the actions and communication from human counterparts. This chapter explores the current state of the art for Human Robot Interaction (HRI), discussing the tools, algorithms, and methods being explored. Representative use cases are discussed to better understand what can be accomplished in today’s manufacturing environment and what challenges could be faced. The concerns around safetySafety in manufacturing, ethics, and unintended consequences are identified. Finally, the chapter looks ahead at the obstacles that still need to be overcome before HRI can be fully scalable and widely used.