• DocumentCode
    869966
  • Title

    Vision-based force measurement

  • Author

    Greminger, Michael A. ; Nelson, Bradley J.

  • Author_Institution
    Dept. of Mech. Eng., Minnesota Univ., Minneapolis, MN, USA
  • Volume
    26
  • Issue
    3
  • fYear
    2004
  • fDate
    3/1/2004 12:00:00 AM
  • Firstpage
    290
  • Lastpage
    298
  • Abstract
    This paper demonstrates a method to visually measure the force distribution applied to a linearly elastic object using the contour data in an image. The force measurement is accomplished by making use of the result from linear elasticity that the displacement field of the contour of a linearly elastic object is sufficient to completely recover the force distribution applied to the object. This result leads naturally to a deformable template matching approach where the template is deformed according to the governing equations of linear elasticity. An energy minimization method is used to match the template to the contour data in the image. This technique of visually measuring forces we refer to as vision-based force measurement (VBFM). VBFM has the potential to increase the robustness and reliability of micromanipulation and biomanipulation tasks where force sensing is essential for success. The effectiveness of VBFM is demonstrated for both a microcantilever beam and a microgripper. A sensor resolution of less than +/-3 nN for the microcantilever and +/-3 mN for the microgripper was achieved using VBFM. Performance optimizations for the energy minimization problem are also discussed that make this algorithm feasible for real-time applications.
  • Keywords
    computer vision; force measurement; grippers; image matching; minimisation; biomanipulation tasks; contour data; energy minimization method; force distribution; governing equations; linear elasticity; linearly elastic object; microcantilever beam; microgripper; micromanipulation; reliability; robustness; template matching; vision based force measurement; Biosensors; Elasticity; Energy resolution; Equations; Force measurement; Force sensors; Grippers; Minimization methods; Optimization; Robustness; Algorithms; Artificial Intelligence; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Biological; Pattern Recognition, Automated; Physical Examination; Reproducibility of Results; Sensitivity and Specificity; Stress, Mechanical; Transducers; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2004.1262305
  • Filename
    1262305