Does Personality Matter in Robot-Moderated Collaboration? Exploring the Personality Role in AR-Enabled Human-to-Human Tasks

Abstract

While collaborative robots (cobots) are designed to augment industrial workflows, their integration is often hindered by not accounting for the individual personality traits that influence human-to-human collaboration. Although personality is a primary driver of trust and coordination, it remains underexplored in multi-agent settings in which a robot serves as an agent moderating human-to-human collaboration. To investigate this, we designed an augmented reality (AR) interface to facilitate human-to-human collaboration moderated by a cobot. Using a gamified pick-and-place task, we examined how personality influences workers' behavior and conflict resolution in a shared workspace. Results from a study with 16 participants, split into 8 pairs of workers, indicate that extraversion/introversion, in particular, was associated with differences in interaction strategies and perceptions of workload. Our findings suggest that future AR-enabled multiagent workflows should consider personality variability to better support collaborative settings.