How Are You Feeling?: Characterization and Analysis of Human Factors in Multi-Human Multi-Robot Collaborative Tasks

Collaborative robots have been employed in a wide range of applications across industries, especially as the transition continues into Industry 5.0. As this new industrial revolution occurs, human-centricity becomes an ever-increasing focus, and the need for a developed understanding of how robot behaviors affect the fundamental human factors of trust, comfort, and acceptance in human-robot collaborative contexts grows. While many efforts have been conducted in this area, what remains relatively understudied on this topic is when robots are working with human workers in a Multi-Human Multi-Robot (MHMR) environment. In this work, we present a framework and develop an experimental platform to collect humans' multimodal physical and physiological biometrics information in order to characterize human factors in MHMR interaction. The electrocardiograms, galvanic skin response, pupillometry, and electromyography signals are acquired during the MHMR collaborative manufacturing process. Experimental results and analysis suggest that human workers' responses to different robot behaviors can be dynamically and quantitatively characterized in MHMR collaboration. This work is a cornerstone for further modeling and understanding of human factors (e.g., trust, comfort, and acceptance) to improve collaboration efficiency for MHMR partnerships in Industry 5.0 contexts. Future directions of this study are also discussed.