• DocumentCode
    2386062
  • Title

    Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

  • Author

    Kazmi, Wajahat ; Ridao, Pere ; Ribas, David ; Hernandez, E.

  • Author_Institution
    Dept. of Comput. Eng., Univ. of Girona, Girona, Spain
  • fYear
    2009
  • fDate
    12-17 May 2009
  • Firstpage
    3595
  • Lastpage
    3600
  • Abstract
    In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions.
  • Keywords
    Hough transforms; Kalman filters; dams; mobile robots; object detection; robot vision; sonar imaging; underwater vehicles; Hough transform; dam inspection tasks; dam wall detection; dam wall tracking; extended Kalman filter; mechanically scanned imaging sonar; polar image scans; underwater robot; water tank conditions; Cameras; Inspection; Remotely operated vehicles; Robot kinematics; Robot sensing systems; Robot vision systems; Robotics and automation; Service robots; Sonar detection; Underwater tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
  • Conference_Location
    Kobe
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-4244-2788-8
  • Electronic_ISBN
    1050-4729
  • Type

    conf

  • DOI
    10.1109/ROBOT.2009.5152691
  • Filename
    5152691