• DocumentCode
    3266033
  • Title

    Landmark Pair based Localization for Intelligent Vehicles using Laser Radar

  • Author

    Wu, Shun-Xi ; Yang, Ming

  • Author_Institution
    Shanghai Jiao Tong Univ., Shanghai
  • fYear
    2007
  • fDate
    13-15 June 2007
  • Firstpage
    209
  • Lastpage
    214
  • Abstract
    Localization, namely pose estimation is of great importance in the research of intelligent vehicles. In this paper, after a simple overview of existing methods, a method of laser radar localization based on landmark pairs (L3P) is presented, which is an improved algorithm of localization based on landmarks to overcome problems of traditional methods, such as low reliability and low robustness of landmark detection, etc. This algorithm has been verified on both synthetic data and real range data in the outdoor environment. Experimental results demonstrate its high accuracy, high robustness to noises and low computation.
  • Keywords
    Kalman filters; mobile robots; nonlinear filters; object detection; optical radar; path planning; pose estimation; extended Kalman filter; intelligent vehicle; landmark pair detection; laser radar localization; mobile robot; pose estimation; Intelligent vehicles; Laser radar; Motion estimation; Noise robustness; Radar detection; Radar tracking; Shape; State estimation; Vehicle detection; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2007 IEEE
  • Conference_Location
    Istanbul
  • ISSN
    1931-0587
  • Print_ISBN
    1-4244-1067-3
  • Electronic_ISBN
    1931-0587
  • Type

    conf

  • DOI
    10.1109/IVS.2007.4290116
  • Filename
    4290116