CAREER: Human Factors and Task Scheduling for Multi-Human Multi-Robot Collaborative Manufacturing in Industry 5.0 Contexts

Robotics plays a significant role in a wide range of manufacturing systems and tasks, especially in emerging Industry 5.0 contexts, where the robots’ cognitive computing capabilities are merged with human workers’ intelligence and resourcefulness as well as manufacturing systems in cooperative operations. Industry 5.0 is an inevitable next industrial revolution, in which the personal human touch is promoted in addition to automation and efficiency characterized in Industry 4.0. This Faculty Early Career Development Program (CAREER) award supports research that will focus on advancing the empowerment, personalization, and diversity of human workers by leveraging the value of human factors and state-of-the-art robotics technologies for multi-human multi-robot collaborative manufacturing in Industry 5.0 contexts. At the heart of the future of manufacturing, human wellbeing is placed at the center of the manufacturing process when pursuing the optimal balance of efficiency and productivity. To alleviate this challenge, the research project will develop a synergistic computational framework including the characterization, modeling, implementation, and assessment of human factors and task scheduling to facilitate fundamental and creative advances for both collaborative manufacturing efficiency and human wellbeing in human-robot partnerships. In addition, the research will be complemented by a scalable educational program (including pre-university education, college student mentoring, and new curriculum development), which will foster and empower next-generation scientists and engineers, especially those from underrepresented groups, by engaging them in learning and implementing leading-edge robotics and manufacturing technologies in real-world applications. The objective of this research is to advance multi-human multi-robot collaborative manufacturing in Industry 5.0 contexts by establishing a synergistic human factors-based task scheduling framework. The major questions to be addressed are (1) How can human factors in multi-human multi-robot collaboration be parameterized and modeled? (2) How can the multi-human multi-robot collaborative manufacturing processes and task scheduling be optimized? and (3) How will the developed framework be validated and assessed in multi-human multi-robot collaborative tasks? To address these, the project involves the creation of new computational models to quantitatively analyze human factors using multimodal behavioral and physiological biometrics information. Then a synergistic human factors-based task scheduling framework will be built for the interdependent human-robot partnerships to improve collaboration efficiency. User studies will be conducted to testify and evaluate the developed approaches through real-world multi-human multi-robot collaborative manufacturing tasks. This research will contribute toward new knowledge and understanding of human factors, task scheduling, and robot autonomy in manufacturing systems integration by leveraging interdisciplinary perspectives from robotics, automation, manufacturing, engineering, and cognitive ergonomics.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.