• DocumentCode
    1423586
  • Title

    Gesture Recognition Based on Localist Attractor Networks with Application to Robot Control [Application Notes]

  • Author

    Yan, Rui ; Tee, Keng Peng ; Chua, Yuanwei ; Li, Haizhou ; Tang, Huajin

  • Author_Institution
    Inst. for Infocomm Res., Singapore, Singapore
  • Volume
    7
  • Issue
    1
  • fYear
    2012
  • Firstpage
    64
  • Lastpage
    74
  • Abstract
    In this work, we proposed an online gesture recognition method based on LAN. It was employed to recognize human gestures using streams of feature vectors extracted from real-time sensory data. As an application, the gesture recognition system was used to instruct the robot to execute the predefined commands such as moving in different directions, changing speed, stopping and so on. Experimental results showed a high accuracy in controlling the mobile robot using gesture recognition. This system provides a flexible and easy-to-use human-robot interface to control a robot. The user only needs to demonstrate all gesture patterns a few times before starting the control tasks. The robot is able to memorize all patterns and recognize a given gesture. Furthermore, in order to define a new pattern corresponding to a new control task, users only need to demonstrate this pattern. It is advantageous in the areas of service robots since many of them will be operated by non-expert users.
  • Keywords
    control engineering computing; feature extraction; gesture recognition; human-robot interaction; mobile robots; service robots; feature vectors extraction; human gesture recognition; human-robot interface; localist attractor networks; mobile robot control; online gesture recognition method; real-time sensory data; robot control; service robots; Feature extraction; Gesture recognition; Human factors; Mathematical model; Robot sensing systems;
  • fLanguage
    English
  • Journal_Title
    Computational Intelligence Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1556-603X
  • Type

    jour

  • DOI
    10.1109/MCI.2011.2176767
  • Filename
    6132215