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

Gaze automation in social robots is pivotal for enhancing Human-Robot Interaction (HRI) by promoting engagement, intuition, and effectiveness in communication. This paper investigates whether different gaze patterns from a Furhat robot can lead to more effective, natural and engaging interactions. Our results indicate that gaze manipulations based on gaze patterns from human-human interaction positively impact user perceptions compared to the neutral and random conditions. Participants rate the anthropomorphism and animacy of the robot in the experimental condition. 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.
Research areas:
Type of Publication:
In Proceedings
Book title:
20th IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO 2024)
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