Engagement and Mind Perception Within Human-Robot Interaction: A Comparison Between Elderly and Young Adults

摘要

People can feel engaged and attribute human-like traits when interacting with a social robot and reveal this unconsciously to observers. Studies have suggested that behavioral signals such as facial expressions, posture, speech and laughter play an important role in identifying engagement in Human-Robot Interaction (HRI), however the effect of these factors in different age groups, as well as their relationship with mind attribution towards robots remains unclear. This study examined 24 elderly people and 24 university students on facial expressions, laughter and speech during an interaction with a NAO-robot. In addition, self-reported engagement level and mind perception scores were collected after the interaction and analyzed. Results showed that elderly had a significantly lower report of engagement with the robot, which was positively correlated with their perception of mind capacity in the robot. Furthermore, for both elderly and students, there was a negative trend between self-reported mind perception and observed behavioral engagement with the robot. Findings of this study could be employed in the design and evaluation of future HRI scenarios.