• DocumentCode
    2334166
  • Title

    Contour reconstruction using recursive smoothing splines - experimental validation

  • Author

    Piccolo, G. ; Karasalo, M. ; Kragic, D. ; Hu, X.

  • Author_Institution
    R. Inst. of Technol., Stockholm
  • fYear
    2007
  • fDate
    Oct. 29 2007-Nov. 2 2007
  • Firstpage
    2071
  • Lastpage
    2076
  • Abstract
    In this paper, a recursive smoothing spline approach for contour reconstruction is studied and evaluated. Periodic smoothing splines are used by a robot to approximate the contour of encountered obstacles in the environment. The splines are generated through minimizing a cost function subject to constraints imposed by a linear control system and accuracy is improved iteratively using a recursive spline algorithm. The filtering effect of the smoothing splines allows for usage of noisy sensor data and the method is robust to odometry drift. Experimental evaluation is performed for contour reconstruction of three objects using a SICK laser scanner mounted on a PowerBot from ActivMedia Robotics.
  • Keywords
    collision avoidance; image reconstruction; linear systems; mobile robots; robot vision; smoothing methods; splines (mathematics); ActivMedia Robotics; PowerBot; SICK laser scanner; contour reconstruction; cost function; encountered obstacle; filtering effect; linear control system; noisy sensor data; odometry drift; periodic smoothing spline; recursive smoothing spline; Control systems; Cost function; Filtering; Iterative algorithms; Performance evaluation; Power lasers; Robots; Robustness; Smoothing methods; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4244-0912-9
  • Electronic_ISBN
    978-1-4244-0912-9
  • Type

    conf

  • DOI
    10.1109/IROS.2007.4399044
  • Filename
    4399044