Vision-based force measurement

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 elast...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2004-03, Vol.26 (3), p.290-298
Main Authors: Greminger, M.A., Nelson, B.J.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Biosensors
Elasticity
Energy resolution
Equations
Force measurement
Force sensors
Grippers
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Mathematical models
Minimization methods
Models, Biological
Optimization
Pattern Recognition, Automated
Physical Examination - instrumentation
Physical Examination - methods
Reproducibility of Results
Robustness
Sensitivity and Specificity
Stress, Mechanical
Studies
Transducers
User-Computer Interface
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Summary: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.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2004.1262305