The Effect of Expressive Robot Behavior on Users' Mental Effort: A Pupillometry Study

Robots are becoming part of our social landscape. Social interaction with humans must be efficient and intuitive to understand because nonverbal cues make social interactions between humans and robots more efficient. This study measures mental effort to investigate what factors influence the intuitive understanding of expressive nonverbal robot motions. Fifty participants were asked to watch, while their pupil response and gaze were measured with an eye tracker, eighteen short video clips of three different robot types while performing expressive robot behaviors. Our findings indicate that the appearance of the robot, the viewing angle, and the expression shown by the robot all influence the cognitive load, and therefore, they may influence the intuitive understanding of expressive robot behavior. Furthermore, we found differences in the fixation time for different features of the different robots. With these insights, we identified possible improvement directions for making interactions between humans and robots more efficient and intuitive.