Good Looking: How Gaze Patterns affect Users' Perceptions of an Interactive Social Robot

Vidya Somashekarappa, Christine Howes, Asad B. Sayeed

Abstract: Gaze automation in social robots is pivotal for enhancing Human-Robot Interaction (HRI) by promoting engagement and effectiveness in communication. This paper investigates whether different gaze patterns from a Furhat robot can lead to more effective, natural and engaging interactions. As the robots are integrating increasingly in human-rich environments, it is important to exhibit social cues to be perceived as a collaborative and socially-adaptive member. The experiment consisting of random, experimental and neutral conditions are rated for anthropomorphism, animacy, likeability, intelligence and safety by the participants after each session. The results indicate that gaze manipulations based on different gaze patterns from human-human interaction positively impact user perceptions in experimental conditions compared to the neutral and random scenarios. The findings contribute to understanding the impact of robot gaze on user perceptions and engagement, offering insights for the design and improvement of interactive social robots.

External IDs:dblp:conf/arso/SomashekarappaH24