Robots That Play with a Child: Application of an Action Decision Model Based on Mental State Estimation

Abstract

There has been many problems in situations surrounding children such as child neglect, deterioration in the quality of play, etc. We believe that robotic playmates would greatly help to solve these problems. In this paper we propose a playmate robot system that can play with a child. Unlike many therapeutic service robots, our proposed playmate system is implemented as a functionality of the domestic service robot with a high degree-of-freedom. This means that the robot can play with children at a high level, i.e., beyond a therapeutic effect, using its physical features. To sustain the player's interest in the system, we also propose an action selection strategy based on a transition model of the child's mental state. The robot can estimate the child's state and select an appropriate action in the course of play. Part of the proposed algorithms was implemented on a real robot platform, and experiments were carried out to design and evaluate the proposed system.