• DocumentCode
    2524586
  • Title

    Autonomous visual self-localization in completely unknown environment

  • Author

    Sadeghi-Tehran, Pouria ; Behera, Sasmita ; Angelov, Plamen ; Andreu, Javier

  • Author_Institution
    InfoLab21, Lancaster Univ., Lancaster, UK
  • fYear
    2012
  • fDate
    17-18 May 2012
  • Firstpage
    90
  • Lastpage
    95
  • Abstract
    In this paper, a novel approach to visual self-localization in an unknown environment is presented. The proposed method makes possible the recognition of new landmark without using GPS or any other communication links or pre-training. An image-based self-localization technique is used to automatically label landmarks that are detected in real-time using a computationally efficient and recursive algorithm. Real-time experiments are carried in outdoor environment at Lancaster University using a real mobile robot Pioneer 3DX in order to build a map the local environment without using any communication links. The presented experimental results in real situations show the effectiveness of the proposed method.
  • Keywords
    image recognition; mobile robots; robot vision; Pioneer 3DX mobile robot; autonomous visual self-localization; image-based self-localization technique; landmark labeling; landmark recognition; local environment mapping; recursive algorithm; Fires; Global Positioning System; Humans; KDE; KDE Cauchy Kernel; autonomous navigation; mobile robot; visual-based landmarks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolving and Adaptive Intelligent Systems (EAIS), 2012 IEEE Conference on
  • Conference_Location
    Madrid
  • Print_ISBN
    978-1-4673-1728-3
  • Electronic_ISBN
    978-1-4673-1726-9
  • Type

    conf

  • DOI
    10.1109/EAIS.2012.6232811
  • Filename
    6232811