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Using real-time recognition of human-robot interaction styles for creating adaptive robot behaviour in robot-assisted play

Abstract

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ALIFE.2009.4937693This paper presents an application of the Cascaded Information Bottleneck Method for real-time recognition of Human-Robot Interaction styles in robot-assisted play. This method, that we have developed, is implemented here for an adaptive robot that can recognize and adapt to children's play styles in real time. The robot rewards well-balanced interaction styles and encourages children to engage in the interaction. The potential impact of such an adaptive robot in robot-assisted play for children with autism is evaluated through a study conducted with seven children with autism in a school. A statistical analysis of the results shows the positive impact of such an adaptive robot on the children's play styles and on their engagement in the interaction with the robot

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