• DocumentCode
    2585341
  • Title

    Natural feature based localization in forested environments

  • Author

    Song, Meng ; Sun, Fengchi ; Iagnemma, Karl

  • Author_Institution
    Coll. of Software, Nankai Univ., Tianjin, China
  • fYear
    2012
  • fDate
    7-12 Oct. 2012
  • Firstpage
    3384
  • Lastpage
    3390
  • Abstract
    This paper presents a new feature based scan matching method for solving 6D localization problem in forested environments. The proposed registration process includes two steps. First, the largest group of approximately parallel tree trunk features is utilized to align successive scans along the five dimensions except z direction. Tree correspondences are established by matching point patterns which are abstracted from the position relationships of trees. The optimal 5D transformation is thus determined based on the axes of two key tree pairs which are selected by evaluating their ability of tree alignment. Second, we assign the ground points of two scans into a grid of cells, and minimize z-direction difference of points in shared cells. The experimental results on data collected in real forested environments have demonstrated the effectiveness of this method.
  • Keywords
    SLAM (robots); image matching; image registration; mobile robots; optical scanners; pose estimation; robot vision; vegetation; 5D transformation; 6D localization problem; feature based scan matching method; forested environments; matching point patterns; mobile robots; parallel tree trunk features; pose determination; pose tracking; registration process; relative localization; tree alignment; z-direction difference; Accuracy; Feature extraction; Manganese; Pattern matching; Robot kinematics; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on
  • Conference_Location
    Vilamoura
  • ISSN
    2153-0858
  • Print_ISBN
    978-1-4673-1737-5
  • Type

    conf

  • DOI
    10.1109/IROS.2012.6385542
  • Filename
    6385542