Accommodating and Assisting Human Partners in Human-Robot Collaborative Tasks through Emotion Understanding
Hope Diamantopoulos, Weitian Wang
Abstract
Human-robot collaboration is inevitable in future smart manufacturing. In order to ensure safe human-robot collaboration, we develop a transfer learning-based approach to teach the robot to understand human emotions in smart manufacturing contexts. Our approach enables the robot to accurately understand human emotions and accommodate its human partner with corresponding assisting actions in collaborative tasks. This allows for improved collaboration-safety and enhanced ergonomics in human-robot partnerships. Experimental results and evaluations demonstrate that the robot can precisely understand human emotions in real time and effectively assist its human partner in real-world co-assembly tasks. Future work for this study is also discussed.