A STEREO VISION-BASED BIN PICKING SYSTEM USING HOPFIELD NEURAL NETWORKS
In this paper, a new machine vision algorithm for close-range position sensing and bin picking is presented where a Hopfield Neural Network (HNN) is used for the stereo matching process. Stereo Matching is formulated as an energy minimization task and this minimization is accomplished using the HNNs. Various other important aspects of this Vision System are discussed including camera calibration and objects localization using a clustering algorithm.
hopfield neural network machine vision calibration stereo vision 3d reconstruction