ERI: An Emotion-Based Robotic Behavior Optimization System for Comfortable and Friendly Human-Robot Collaboration

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This Engineering Research Initiation (ERI) award will support research that will contribute new knowledge related to comfortable and friendly human-robot collaboration in manufacturing, promoting the development progress of robotics and advancing human-robot interaction technologies. Collaborative robots in manufacturing work with humans on repetitive and dangerous tasks to improve efficiency and productivity. However, stiff and mechanical interaction behaviors of the current robots lower the naturalness and flexibility of the collaboration process. Prolonged exposure to working with such robots will cause significant stress among human workers. Therefore, it is crucial to improve the interaction behaviors of the collaborative robot. This award supports fundamental research to provide needed knowledge for the development of an emotion-based robotic behavior optimization system. It aims to turn the current collaborative robot into an empathetic and friendly working companion that can adaptively adjust its interaction behaviors for facilitating comfortable and friendly collaboration processes. Results from this research can further benefit the U.S. economy and society by bringing humans back to manufacturing automation. The interdisciplinary research activities in this project will help broaden the participation of underrepresented groups in engineering research and positively impact engineering education.To realize a human-centered, comfortable, and friendly collaboration between the human and the robot in manufacturing, this project will develop an emotion-based robotic behavior optimization system. The system can turn the current collaborative robot into a smart companion which can not only understand and respond to human intentions and emotions but also adaptively optimize its actions to facilitate comfortable and friendly collaboration in manufacturing tasks. This project will: (1) develop a new computational model to let the robot understand human intentions and measure human emotions, (2) develop an interaction system to enable the collaborative robot to intelligently respond to human emotions and optimize its actions for a natural and flexible human-robot collaboration, and (3) conduct real-world experiments to validate and assess the effectiveness, efficiency, and human acceptance of the developed system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.