Human-Centric Digital Twins: Advancing Safety and Ergonomics in Human-Robot Collaboration

Abstract

Human-Robot Collaboration combines the reliability of robots with human adaptability. It is a prime candidate to respond to the trend of Mass Customization which requires frequent reconfiguration with variable lot sizes. But the close contact between humans and robots creates new safety risks and ergonomic factors like robot-induced stress need to be considered. Therefore we propose a human-centric Digital Twin framework, where information about the human is stored and processed in a dedicated Digital Twin and can be transmitted to the robot's Digital Twin for human-aware adaptations. We envision and briefly discuss three possible applications. Our framework has the potential to advance collaborative robotics but inherits technical challenges that come with Digital Twin based approaches and human modelling.