Artificial Intelligence and Robotics Commons^™

Autonomous Robot Navigation In Unknown Terrains Using Parallel Numerical Artificial Potential Fields, John C. Schneider

Computer Science Theses & Dissertations

We present a new artificial potential field formulation for resolution complete robot navigation that unifies the purely geometric path planning problem with the lower level force control problem. Our formulation is designed for numerical computation over a massively parallel mesh of processors and is responsive to newly discovered terrain features. It does not suffer from many of the problems commonly associated with potential fields and with adequate resolution provides provably correct, collision free convergence to the goal. In addition, our formulation supports many desirable, practical features required for implementation, such as bounded actuator torques, attainable incremental constructability, realizable computation and …

Real Time Texture Analysis From The Parallel Computation Of Fractal Dimension, Halford I. Hayes Jr.

Computer Science Theses & Dissertations

The discrimination of texture features in an image has many important applications: from detection of man-made objects from a surrounding natural background to identification of cancerous from healthy tissue in X-ray imagery. The fractal structure in an image has been used with success to identify these features but requires unacceptable processing time if executed sequentially.

The paradigm of data parallelism is presented as the best method for applying massively parallel processing to the computation of fractal dimension of an image. With this methodology, and sufficient numbers of processors, this computation can reach real time speeds necessary for many applications. A …

Recognition Of Quadric Surfaces From Range Data: An Analytical Approach, Ivan X. D. D'Cunha

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, a new technique based on analytic geometry for the recognition and description of three-dimensional quadric surfaces from range images is presented. Beginning with the explicit representation of quadrics, a set of ten coefficients are determined for various three-dimensional surfaces. For each quadric surface, a unique set of two-dimensional curves which serve as a feature set is obtained from the various angles at which the object is intersected with a plane. Based on a discriminant method, each of the curves is classified as a parabola, circle, ellipse, hyperbola, or a line. Each quadric surface is shown to be …

Formant Estimation From Dctc's Using A Feedforward Neural Network, Shubhangi U. Kelkar

Electrical & Computer Engineering Theses & Dissertations

Formants are the natural frequencies of the human vocal tract. Existing methods for estimating formants from speech signals are computationally complex and subject to errors for certain type of speech sounds. This thesis describes a method for estimating vowel formant frequencies from Discrete Cosine Transform Coefficients (DCTC's), a form of cepstral coefficients, using a feedforward neural network with back-propagation training. Experimental results are based on a large multispeaker data base. The results are obtained for both a linear transformation and a feedforward neural network with a nonlinear hidden layer. In general, the neural network transformation is superior to the linear …

Monitoring Computer Systems: An Intelligent Approach, Myron Zhihong Xu

Computer Science Theses & Dissertations

Monitoring modern computer systems is increasingly difficult due to their peculiar characteristics. To cope with this situation, the dissertation develops an approach to intelligent monitoring. The resulting model consists of three major designs: representing targets, controlling data collection, and autonomously refining monitoring performance. The model explores a more declarative object-oriented model by introducing virtual objects to dynamically compose abstract representations, while it treats conventional hard-wired hierarchies and predefined object classes as primitive structures. Taking the representational framework as a reasoning bed, the design for controlling mechanisms adopts default reasoning backed up with ordered constraints, so that the amount of data …

Reasoning By Analogy In A Multi-Level System Architecture For The Design Of Mechanisms, Ghassan F. Issa

Computer Science Theses & Dissertations

Since the first attempts to integrate AI technology and engineering design nearly two decades ago, few expert systems have been shown to demonstrate sufficient reasoning capabilities to solve real-world design problems. The complex nature of design, the lack of understanding of the design process, and the limitations of current expert system technology have all been shown to have adverse effects on the maturity of this research area. Therefore, our direction in this research concentrates on understanding the design process, investigating a novel area of research focusing on creative design, and incorporating the results into a system model feasible for production …

Kinematic Synthesis Of Deployable-Foldable Truss Structures Using Graph Theory, Dirk B. Warnaar

Mechanical & Aerospace Engineering Theses & Dissertations

A graph theoretic approach is applied to the conceptual design of deployable truss structures. The characteristics that relate to the inter-connectivity of the elements of a deployable truss structure can be captured in a schematic representation, called a graph. A procedure is presented that enables the exhaustive generation of these graphs for structures of any given number of nodes and links and which are foldable onto a plane or onto a line.

A special type of truss structures, called truss modules, is presented. Graphs of this class of structures form a subset of the graphs of truss structures. Two procedures …

Effectiveness Analysis Of Knowledge Bases, Shensheng Zhao

Computer Science Theses & Dissertations

Knowledge base systems (expert systems) are entering a critical stage as interest spreads from university research to practical applications. If knowledge base systems are to withstand this transition, special attention must be paid to checking their effectiveness. The issue of effectiveness analysis of knowledge base systems has been largely ignored and few works have been published in this field. This dissertation shows how the effectiveness of a knowledge base system can be defined, discussed and analyzed at the knowledge base system level and the knowledge base level. We characterize the effectiveness of a knowledge base system in terms of minimality, …

Integration Of Abductive And Deductive Inference Diagnosis Model And Its Application In Intelligent Tutoring System, Jingying Zhang

Computer Science Theses & Dissertations

This dissertation presents a diagnosis model, Integration of Abductive and Deductive Inference diagnosis model (IADI), in the light of the cognitive processes of human diagnosticians. In contrast with other diagnosis models, that are based on enumerating, tracking and classifying approaches, the IADI diagnosis model relies on different inferences to solve the diagnosis problems. Studies on a human diagnosticians' process show that a diagnosis process actually is a hypothesizing process followed by a verification process. The IADI diagnosis model integrates abduction and deduction to simulate these processes. The abductive inference captures the plausible features of this hypothesizing process while the deductive …

An Artificial Neural Approach To The Decomposition Problem, Chandrashekar L. Masti

Electrical & Computer Engineering Theses & Dissertations

The goal of this thesis is to develop an artificial neural approach toward addressing the intractability involved with the decomposition problem. The search for the lattice of substitution property (s. p.) partitions essential to decompositions is cast into the framework of constraint satisfaction. An artificial neural network is developed to provide solutions by performing optimization of a mathematically derived objective function over the problem space. The issue of transitivity is verified to belong to a class of problems beyond the scope of solvability for conventional quadratic-order constraint satisfaction neural networks. A theorem is stated and proved establishing that third-order correlations …

A Classification Approach For Automated Reasoning Systems--A Case Study In Graph Theory, Rong Lin

Computer Science Theses & Dissertations

Reasoning systems which create classifications of structured objects face the problem of how object descriptions can be used to reflect their components as well as relations among these components. Current reasoning systems on graph theory do not adequately provide models to discover complex relations among mathematical concepts (eg: relations involving subgraphs) mainly due to the inability to solve this problem. This thesis presents an approach to construct a knowledge-based system, GC (Graph Classification), which overcomes this difficulty in performing automated reasoning in graph theory. We describe graph concepts based on an attribute called Linear Recursive Constructivity (LRC). LRC defines classes …