• DocumentCode
    2027890
  • Title

    Combining synchrony and shape detection to sustain the robot focus of attention on a selected human partner

  • Author

    Grand, Caroline ; Mostafaoui, Ghiles ; Hasnain, S.K. ; Gaussier, Philippe

  • Author_Institution
    Neurocybernetic T, Univ. of Cergy-Pontoise, Cergy-Pontoise, France
  • fYear
    2013
  • fDate
    18-22 Aug. 2013
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    The present study deals with the problematic of attentional mechanism allowing to initiate and to maintain Human Robot Interactions (HRI) by orienting the robot´s visual focus on interacting human partners. In our previous work, we took inspiration from human psychological and neurological data which suggest that synchrony is an important parameter for human-human interaction. We proposed synchrony as a way of interacting and presented a synchrony-based architecture capable of selecting the human partner and of locating the focus of attention. To deal with the problematic of initiating the HRI, we proposed, in our recent works, a neural model permitting to focus the robot visual attention on a selected partner on the basis of synchrony detection between its own dynamics and the human movements. This model maintain the interaction and the robot´s focus of attention while the partner moves in synchrony. Consequently, the interaction is interrupted if the partner stops moving. For a more realist HRI, the agents have to be able to switch their roles (turn tacking), as a result, they could alternate moving and static interaction phases. In this case, we propose here to complete the previous neural model by adding a shape based attentional mechanism. After initiating the interaction on the basis of synchrony, the robot will automatically learn to recognize the selected partner and maintain its attention with the human during unsynchronized phases of interaction.
  • Keywords
    human-robot interaction; image motion analysis; learning systems; neurocontrollers; robot vision; HRI; human movement; human psychological data; human robot interaction; human-human interaction; interacting human partner; moving interaction phase; neural model; neurological data; partner recognition; robot focus of attention; robot learning; robot visual attention; robot visual focus; shape based attentional mechanism; shape detection; static interaction phase; synchrony-based architecture; turn tacking; Conferences; Mobile robots; Object recognition; Robot kinematics; Shape; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Development and Learning and Epigenetic Robotics (ICDL), 2013 IEEE Third Joint International Conference on
  • Conference_Location
    Osaka
  • Type

    conf

  • DOI
    10.1109/DevLrn.2013.6652529
  • Filename
    6652529