• DocumentCode
    1637859
  • Title

    Is that me? Sensorimotor learning and self-other distinction in robotics

  • Author

    Schillaci, Guido ; Hafner, Verena V. ; Lara, Bruno ; Grosjean, M.

  • Author_Institution
    Cognitive Robot. Group, Humboldt-Univ. zu Berlin, Berlin, Germany
  • fYear
    2013
  • Firstpage
    223
  • Lastpage
    224
  • Abstract
    In order to have robots interact with other agents, it is important that they are able recognize their own actions. The research reported here relates to the use of internal models for self-other distinction. We demonstrate how a humanoid robot, which acquires a sensorimotor scheme through self-exploration, can produce and predict simple trajectories that have particular characteristics. Comparing these predictions to incoming sensory information provides the robot with a basic tool for distinguishing between self and other.
  • Keywords
    humanoid robots; learning (artificial intelligence); mobile robots; Nao humanoid robot; robotics; self-other distinction; sensorimotor learning; sensorimotor scheme; sensory information; trajectory prediction; trajectory production; Inverse problems; Predictive models; Robot kinematics; Robot sensing systems; Training; Trajectory; Internal simulations; inverse and forward models; self-advantage; self-other distinction; sensorimotor learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Human-Robot Interaction (HRI), 2013 8th ACM/IEEE International Conference on
  • Conference_Location
    Tokyo
  • ISSN
    2167-2121
  • Print_ISBN
    978-1-4673-3099-2
  • Electronic_ISBN
    2167-2121
  • Type

    conf

  • DOI
    10.1109/HRI.2013.6483582
  • Filename
    6483582