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

Abstract

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 factors influencing the intuitive understanding of expressive nonverbal robot motions. Using an eye tracker to measure pupil response and gaze, fifty participants were asked to watch eighteen short video clips featuring three different types of robots 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. Therefore, they may affect the intuitive understanding of expressive robot behavior. Furthermore, we found differences in the fixation time for different features of the various robots. With these insights, we identified possible improvement directions for making interactions between humans and robots more efficient and intuitive.