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Robotic motion learning framework to promote social engagement
Applied Sciences
  • Rachel Burns, George Washington University
  • Myounghoon Jeon, Michigan Technological University
  • Chung Hyuk Park, George Washington University
Document Type
Article
Publication Date
2-1-2018
Disciplines
Abstract

Abstract Imitation is a powerful component of communication between people, and it poses an important implication in improving the quality of interaction in the field of human–robot interaction (HRI). This paper discusses a novel framework designed to improve human–robot interaction through robotic imitation of a participant’s gestures. In our experiment, a humanoid robotic agent socializes with and plays games with a participant. For the experimental group, the robot additionally imitates one of the participant’s novel gestures during a play session. We hypothesize that the robot’s use of imitation will increase the participant’s openness towards engaging with the robot. Experimental results from a user study of 12 subjects show that post-imitation, experimental subjects displayed a more positive emotional state, had higher instances of mood contagion towards the robot, and interpreted the robot to have a higher level of autonomy than their control group counterparts did. These results point to an increased participant interest in engagement fueled by personalized imitation during interaction.

Publisher's Statement

© 2018 by the authors. Article deposited here in compliance with publisher policies. Publisher's version of record: https://doi.org/10.3390/app8020241

Creative Commons License
Creative Commons Attribution 4.0 International
Version
Publisher's PDF
Citation Information
Rachel Burns, Myounghoon Jeon and Chung Hyuk Park. "Robotic motion learning framework to promote social engagement" Applied Sciences Vol. 8 Iss. 2 (2018)
Available at: http://works.bepress.com/philart-jeon/65/