• DocumentCode
    686255
  • Title

    3D Point Clouds Segmentation for Autonomous Ground Vehicle

  • Author

    Habermann, Danilo ; Hata, Alberto ; Wolf, Denis ; Osorio, Fernando Santos

  • Author_Institution
    Mobile Robot. Lab. - LRM/ICMC, Univ. of Sao Paulo, Sao Carlos, Brazil
  • fYear
    2013
  • fDate
    4-8 Dec. 2013
  • Firstpage
    143
  • Lastpage
    148
  • Abstract
    Point clouds segmentation is an essential step to improve the performance of obstacle detection and classification in areas of autonomous ground vehicles and mobile robotics. This paper presents a study and comparison of the performance of segmentation methods using point clouds coming from a 3D laser sensor, more specifically obtained from a Velodyne HDL32.
  • Keywords
    collision avoidance; control engineering computing; mobile robots; optical sensors; telerobotics; 3D laser sensor; 3D point clouds segmentation; Velodyne HDL32; autonomous ground vehicle; mobile robotics; obstacle detection; segmentation methods; Image segmentation; Land vehicles; Laser radar; Lasers; Robot sensing systems; Three-dimensional displays; 3D Lidar; autonomous ground vehicle; point clouds segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing Systems Engineering (SBESC), 2013 III Brazilian Symposium on
  • Conference_Location
    Niteroi
  • Type

    conf

  • DOI
    10.1109/SBESC.2013.43
  • Filename
    6825357
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=686255