• DocumentCode
    3089591
  • Title

    V-GPS(SLAM): vision-based inertial system for mobile robots

  • Author

    Burschka, Darius ; Hager, Gregory D.

  • Author_Institution
    Comput. Interaction & Robotics Laboratory, Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    1
  • fYear
    2004
  • fDate
    26 April-1 May 2004
  • Firstpage
    409
  • Abstract
    We present a novel vision-based approach to simultaneous localization and mapping (SLAM). We discuss it in the context of estimating the 6 DoF pose of a mobile robot from the perception of a monocular camera using a minimum set of three natural landmarks. In contrast to our previously presented V-GPS system, which navigates based on a set of known landmarks, the current approach allows to estimate the required information about the landmarks on-the-fly during the exploration of an unknown environment The method is applicable to indoor and outdoor environments. The calculation is done from the image position of a set of natural landmarks that are tracked in a continuous video stream at frame-rate. An automatic hand-off process allows an update of the set to compensate for occlusions and decreasing reconstruction accuracies with the distance to an imaged landmark. A generic sensor model allows a system configuration with a variety of physical sensors including: monocular perspective cameras, omni-directional cameras and laser range finders.
  • Keywords
    cameras; mobile robots; position control; robot vision; laser range finders; mobile robots; monocular camera perception; monocular perspective cameras; omnidirectional cameras; robot vision; vision-based inertial system; Cameras; Image reconstruction; Laser modes; Laser theory; Mobile robots; Navigation; Robot vision systems; Sensor systems; Simultaneous localization and mapping; Streaming media;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-8232-3
  • Type

    conf

  • DOI
    10.1109/ROBOT.2004.1307184
  • Filename
    1307184