May I Have Your Attention?! Exploring Multitasking in Human-Robot Collaboration

Abstract

Human-robot collaboration promises to free the human to multitask and engage in cognitive work while the robots assists with physical tasks, therefore increasing productivity. However, this collaborative paradigm requires continuous attention from human operators, which could potentially strain their cognitive resources. Excessive attention demands can lead to safety hazards, increased errors, and reduced efficiency. Despite its critical importance, there is limited empirical research on attentional factors in industrial human-robot collaboration. In this study, we explore attentional multitasking in collaborative human-robot assembly settings. Our experimental setup involves participants performing a wire harnessing task with a collaborative robot while simultaneously completing a Go/No-Go test as a secondary task. To observe the effect of multitasking, we varied the difficulty of the secondary task across two levels and analysed its impacts on work performance and workload. Our results confirm threaded cognition theory, suggesting that human-robot collaboration could reduce cognitive capacity by depleting attentional resources, leading to higher errors and cycle times during multitasking. This underscores the importance of a detailed understanding of attentional factors in human-robot collaboration. We discuss our findings and their implications, and provide insights into the adjustment and design of human-robot collaboration tasks in the industry.