• DocumentCode
    2189914
  • Title

    Collaborative calibration: extending shape from motion calibration

  • Author

    Voyles, Richard M. ; Khosla, Pradeep K.

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    4
  • fYear
    1997
  • fDate
    20-25 Apr 1997
  • Firstpage
    2795
  • Abstract
    In this paper we summarize recent research results from a new technique of sensor calibration called shape-from-motion calibration. We first present the basic technique, which is an eigenspace analysis, and show that it includes the rigor of least squares without the full burden of measuring all the applied inputs. Next we present new research that removes another constraint of the calibration technique and extends the robustness to cover systems with slight nonlinearities
  • Keywords
    calibration; eigenvalues and eigenfunctions; image recognition; motion estimation; nonlinear systems; robot vision; collaborative calibration; eigenspace analysis; least-squares method; nonlinearities; sensor calibration; shape-from-motion calibration; Calibration; Collaboration; Force sensors; Least squares methods; Manipulators; Matrix decomposition; Mobile robots; Robot sensing systems; Shape; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on
  • Conference_Location
    Albuquerque, NM
  • Print_ISBN
    0-7803-3612-7
  • Type

    conf

  • DOI
    10.1109/ROBOT.1997.606710
  • Filename
    606710