Improving Safety in Human-Robot Collaboration Via Mixed Reality-Augmented Deep Reinforcement Learning

In the context of Industry 5.0, the transition towards a human-centric manufacturing paradigm underscores the importance of interactive collaboration among manufacturing equipment. Ensuring safety in Human-Robot Collaboration (HRC) becomes paramount, with traditional rule-based or physical isolation-based approaches exhibiting limitations in flexibility and synergy. Deep Reinforcement Learning (DRL) holds promise for safe motion planning in unstructured HRC environments; however, challenges such as inadequate state representation, complex scenes, and safety concerns impede its deployment. To address these challenges, we propose a Mixed Reality (MR)-augmented safe HRC framework integrating DRL. This framework incorporates both passive human and proactive human protective measures through deep reinforcement learning. Experimental validations in practical settings demonstrate the effectiveness of the proposed approach.