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A Neural integrated Fuzzy conTroller (NiF-T) which integrates the fuzzy logic representation of human knowledge with the learning capability of neural networks is developed for nonlinear dynamic control problems. NiF-T architecture comprises of three distinct parts: (1) Fuzzy logic Membership Functions (FMF), (2) a Rule Neural Network (RNN), and (3) an(More)
Once segmentation of 3D surface data of a rock pile has been performed, the next task is to determine the visibility of the surface rocks. A region boundary-following algorithm that accommodates irregularly spaced 3D coordinate data is presented for determining this visibility. We examine 3D surface segmentations of laboratory rock piles and determine which(More)
Accurate and efficient monitoring of dynamically changing environments is one of the most important requirements for visual surveillance systems. This paper describes the development of an integrated system for this monitoring purpose. The system consists of multiple omni-directional vision sensors and was developed to address two specific surveillance(More)
Image segmentations have been performed to identify the surface fragmentation of rock piles using 3D surface data, and quantified. The advantages for fragmentation measurement using image analysis are significant and include: quantifying image segmentation performance in isolation of the downstream processes of fragment classification and size distribution(More)
A new " range-space " approach is described for synergistic resolution of both stereovision and reflectance (visual) modeling problems simultaneously. This synergistic approach can be applied to arbitrary camera arrangements with different intrinsic and extrinsic parameters, image types, image resolutions, and image number. These images are analyzed in a(More)
In this paper we present a set of novel methods for image-based modeling using omnidirectional vision sensors. The basic idea is to directly and efficiently acquire plenotpic representations by using omnidi-rectional vision sensors. The three methods from the simplest to the more sophisticated one are listed as Direct Memorization, Discrete Interpolation,(More)
This paper characterizes how well the modular neuro-fuzzy controller, MoNiF, can perform in robotic applications by testing it in a race-car simulator. The performance of this controller is compared with that of a neural network controller NNC and the best programmed c ar the ideal car. During the phase of learning from the ideal car, MoNiF reaches its(More)