• DocumentCode
    2517517
  • Title

    360 Degree multi sensor fusion for static and dynamic obstacles

  • Author

    Schueler, Kai ; Weiherer, Tobias ; Bouzouraa, Essayed ; Hofmann, Ulrich

  • Author_Institution
    Lehrstuhl fuer Datenverarbeitung, Tech. Univ. Muenchen, Munich, Germany
  • fYear
    2012
  • fDate
    3-7 June 2012
  • Firstpage
    692
  • Lastpage
    697
  • Abstract
    In this paper an approach for 360 degree multi sensor fusion for static and dynamic obstacles is presented. The perception of static and dynamic obstacles is achieved by combining the advantages of model based object tracking and an occupancy map. For the model based object tracking a novel multi reference point tracking system, called best knowledge model, is introduced. The best knowledge model allows to track and describe objects with respect to a best suitable reference point. It is explained how the object tracking and the occupancy map closely interact and benefit from each other. Experimental results of the 360 degree multi sensor fusion system from an automotive test vehicle are shown.
  • Keywords
    SLAM (robots); collision avoidance; driver information systems; object tracking; sensor fusion; automotive test vehicle; dynamic obstacle; knowledge model; multireference point tracking system; multisensor fusion; object tracking; occupancy map; static obstacle; Dynamics; Laser modes; Laser radar; Measurement by laser beam; Radar tracking; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium (IV), 2012 IEEE
  • Conference_Location
    Alcala de Henares
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4673-2119-8
  • Type

    conf

  • DOI
    10.1109/IVS.2012.6232253
  • Filename
    6232253