Adaptive robot design with hand and face tracking for use in autism therapy

Authors:
Laura Boccanfuso;Jason M. O'Kane
Affiliations:
Department of Computer Science and Engineering, University of South Carolina, Columbia, South Carolina;Department of Computer Science and Engineering, University of South Carolina, Columbia, South Carolina
Venue:
ICSR'10 Proceedings of the Second international conference on Social robotics
Year:
2010

Citing 3
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Abstract

This research explores interactive games using hand and face tracking with a robot as a tool for autism therapy. The robot is equipped with a head and two arms, each with two degrees of freedom, and a camera. We trained a classifier to detect human hands and subsequently, used this classifier along with a standard face tracker to create two interactive games. In the first game the robot waits for the child to initiate an interaction by raising one or both hands. In the second game, the robot initiates interactions. These games are designed to increase attention, promote turn-taking skills and encourage child-led verbal and non-verbal communication through simple imitative play. This research makes two specific contributions: (1) We present a low-cost robot design which measures and adapts to a child's actions during interactive games and, (2) we train and test a hand detector, based on Haar-like features, which is usable in various kinds of human-robot interactions.