• DocumentCode
    583443
  • Title

    Object and ground classification for a mobile robot in urban environment

  • Author

    Ha Jeong Hyo ; Kim, Sijong ; Chung, Myung Jin

  • Author_Institution
    Dept. of Electr. Eng., KAIST, Daejeon, South Korea
  • fYear
    2012
  • fDate
    17-21 Oct. 2012
  • Firstpage
    2068
  • Lastpage
    2070
  • Abstract
    Recently, An interest about the unmanned vehicles is increasing, and a related research has been actively researched. Application systems using the partial element of technologies are commercialized. The information about surrounding environment should be able to use effectively in order to perform a given task such as robot navigation, path planning, and obstacle avoidance. The essential function for a mobile robot is object perception. This paper proposes an algorithm of object detection using stereo camera. The 3D spatial information is obtained by stereo matching algorithm. The reliability of 3D data is defined according to the distance between the object and the camera, and is used in the filtering process. The geometrical features were analyzed by the continuous characteristic of pixels in image. We achieve classification of ground and object.
  • Keywords
    cameras; image classification; image matching; mobile robots; object detection; remotely operated vehicles; robot vision; 3D data reliability; 3D spatial information; filtering process; geometrical feature analysis; ground classification; mobile robot; object classification; object detection; object perception; pixel continuous characteristics; stereo camera; stereo matching algorithm; unmanned vehicles; urban environment; Algorithm design and analysis; Cameras; Classification algorithms; Reliability; Roads; Sensors; Spatial databases; Ground Rejection; Object Detection; Stereo Matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Systems (ICCAS), 2012 12th International Conference on
  • Conference_Location
    JeJu Island
  • Print_ISBN
    978-1-4673-2247-8
  • Type

    conf

  • Filename
    6393214