Modeling elastic objects with neural networks for vision-based force measurement
Michael A. Greminger, Bradley J. Nelson · 2004
This paper presents a method to model the deformation of an elastic object with an artificial neural network. The neural network is trained directly from images of the elastic object deforming under known loads. Using this process, models can be created for objects such as biological tissues that cannot be modeled by existing techniques. The neural network elastic model is used in conjunction with a deformable template matching algorithm to perform vision-based force measurement (VBFM). We demonstrate this learning method on objects with both linear and nonlinear elastic properties.