An Exploratory Study on People's Intuitive Understanding of Expressive Robot Behavior

Abstract

Robots are anticipated to communicate with humans in our social context. Using nonverbal communication by robots increases communication comprehension because humans intuitively understand such behavior due to their experience of human-human interaction. Thus, this behavior is suitable for studying what makes robot motion intuitive to understand in human-robot interaction (HRI). We study how robot features help humans intuitively grasp expressive robot gestures, concentrating on what makes behavior easy to interpret. After watching eighteen nine-second videos of three robot kinds demonstrating expressive robot actions, 50 participants completed an open-ended survey. Our findings highlight the inputs, mediating factors, and outputs that users reported based on observing examples of expressive robot behavior. These insights are a starting point for analyzing robot behavior from the perspective of intuition and provide a foundation for a theoretical framework for intuition in HRI.