• DocumentCode
    3017511
  • Title

    Gesture recognition using evolution strategy neural network

  • Author

    Hägg, Johan ; Çürüklü, Baran ; Akan, Batu ; Asplund, Lars

  • Author_Institution
    Intell. Sensor Syst., Malardalen Univ., Vasteras
  • fYear
    2008
  • fDate
    15-18 Sept. 2008
  • Firstpage
    245
  • Lastpage
    248
  • Abstract
    A new approach to interact with an industrial robot using hand gestures is presented. System proposed here can learn a first time userpsilas hand gestures rapidly. This improves product usability and acceptability. Artificial neural networks trained with the evolution strategy technique are found to be suited for this problem. The gesture recognition system is an integrated part of a larger project for addressing intelligent human-robot interaction using a novel multi-modal paradigm. The goal of the overall project is to address complexity issues related to robot programming by providing a multi-modal user friendly interacting system that can be used by SMEs.
  • Keywords
    gesture recognition; industrial robots; learning (artificial intelligence); neurocontrollers; ANN training; SME; evolution strategy neural network; hand gesture recognition; industrial robot; intelligent human-robot interaction; multi modal paradigm; product usability; user friendly interacting system; Intelligent sensors; Investments; Manufacturing automation; Manufacturing industries; Manufacturing processes; Neural networks; Orbital robotics; Robot programming; Robotics and automation; Service robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies and Factory Automation, 2008. ETFA 2008. IEEE International Conference on
  • Conference_Location
    Hamburg
  • Print_ISBN
    978-1-4244-1505-2
  • Electronic_ISBN
    978-1-4244-1506-9
  • Type

    conf

  • DOI
    10.1109/ETFA.2008.4638401
  • Filename
    4638401