• DocumentCode
    1558771
  • Title

    Machine vision system for the automatic identification of robot kinematic parameters

  • Author

    Rousseau, Patrick ; Desrochers, Alain ; Krouglicof, Nicholas

  • Author_Institution
    Walsh Autom., Montreal, Que., Canada
  • Volume
    17
  • Issue
    6
  • fYear
    2001
  • fDate
    12/1/2001 12:00:00 AM
  • Firstpage
    972
  • Lastpage
    978
  • Abstract
    This paper presents an efficient, noncontact measurement technique for the automatic identification of the real kinematic parameters of an industrial robot. The technique is based on least-squares analysis and on the Hayati and Mirmirani kinematic modeling convention for closed kinematic chains. The measurement system consists of a single camera mounted on the robot´s wrist. The camera measures position and orientation of a passive target in six degrees of freedom. Target position is evaluated by applying least-squares analysis on an overdetermined system of equations based on the quaternion representation of the finite rotation formula. To enhance the accuracy of the measurement, a variety of image processing functions including subpixel interpolation are applied
  • Keywords
    calibration; computer vision; industrial robots; least squares approximations; parameter estimation; robot kinematics; automatic identification; calibration; closed kinematic chains; finite rotation formula; image processing functions; industrial robot; least-squares analysis; machine vision system; noncontact measurement technique; orientation; overdetermined system; parameter identification; passive target; position; quaternion representation; real kinematic parameters; robot kinematic parameters; single camera; six degrees of freedom; subpixel interpolation; Cameras; Equations; Kinematics; Machine vision; Measurement techniques; Position measurement; Robot vision systems; Robotics and automation; Service robots; Wrist;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.976033
  • Filename
    976033