Estimation of child personality for child-robot interaction

Abstract

We propose a technique to estimate a child's extraversion and agreeableness for social robots that interact with children. The proposed approach observed children's behavior using only the robot's sensors, without any sensor networks in the environment. An RGBD sensor was used to track and identify children's facial expressions. Children's interactions with the robot were observed, such as their distance from the robot and the duration of their eye contact, because such information would provide clues to estimate their personality. Data were collected when a robot, tele-operated by preschool teachers, interacted with kindergarten children individually. The data from 29 children was used to successfully estimate the children's personality compared to chance rates.