@article{Burns18-AS-MotionLearning,
  title = {Robotic Motion Learning Framework to Promote Social Engagement},
  journal = {Applied Sciences},
  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.},
  volume = {8},
  number = {2},
  pages = {241},
  month = feb,
  year = {2018},
  note = {Special Issue "Social Robotics"},
  slug = {bevillmastersthesis},
  author = {Burns, Rachael and Jeon, Myounghoon and Park, Chung Hyuk},
  url = {http://www.mdpi.com/2076-3417/8/2/241},
  month_numeric = {2}
}