Artificial Intelligence and Robotics Commons^™

Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results

Fuzzy Logic Applied To System Control To Enhance Commercial Appliance Performance, Glenn Moffett

Doctoral Dissertations

The purpose of this research is to determine the usefulness of fuzzy logic and fuzzy control when applied to a commercial appliance. Fuzzy logic is a structured, model-free estimator that approximates a function through linguistic input/output associations. Fuzzy rule-based systems apply these methods to solve many types of "real-world" problems, especially where a system is difficult to model, is controlled by a human operator or expert, or where ambiguity or vagueness is common.

This dissertation presents fuzzy sets, fuzzy systems, and fuzzy control, with an example conveying the use of fuzzy control of a consumer product and an overview of …

Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …

Development Of Object-Based Teleoperator Control For Unstructured Applications, Hyunki Cho

Theses and Dissertations

For multi-fingered end effectors in unstructured applications, the main issues are control in the presence of uncertainties and providing grasp stability and object manipulability. The suggested concept in this thesis is object based teleoperator control which provides an intuitive way to control the robot in terms of the grasped object and reduces the operator's conceptual constraints. The general control law is developed using a hierarchical control structure, i.e., human interface I gross motion control level in teleoperation control and fine motion control/object grasp stability in autonomous control. The gross motion control is required to provide the position/orientation of the Super …

Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.

Text Independent Speaker Verification Using Binary-Pair Partitioned Neural Networks, Claude A. Norton Iii

Electrical & Computer Engineering Theses & Dissertations

A method is presented for the application of binary-pair partitioned neural networks to the task of speaker verification. This technique is based on a previously developed neural network classifier for speaker identification.

The main focus of this research was the development and testing of the algorithms necessary to extend the binary-pair partitioning approach from speaker identification to speaker verification. The method is based on the development of a user profile which is obtained from discriminative data provided by the binary-pair partitioned neural networks.

Experimental results are provided which demonstrate the viability of this approach, using the TIMIT speech corpus for …

Survey And Implementation Of Commercial Manual Controllers For A Generic Telerobotics Architecture, Thomas E. Deeter

Theses and Dissertations

The purpose of this study is to determine an input device for the Air Force's generic telerobotics architecture for large aircraft maintenance and repair. One area of concern is the human to machine interface, more specifically, which manual controller should be used for the specified tasks in this architecture. We mailed a survey to 68 companies in order to compile a list of possible input devices that the telerobotics architecture could use. 32 companies responded which gave me enough data to generate a list that described the physical traits of the input devices. We then divided the required tasks into …

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 …

Hardware-Verification Through Logic Extraction, Michael A. Dukes

Theses and Dissertations

A Prolog-based system is described which employs logic-extraction to perform hardware-verification. The extraction rules are built automatically from hierarchical structural VHDL models, enabling the equivalence of a structural VHDL description and a layout specification to be verified. Pin-to-pin critical- path analysis is performed within the logic-extraction process; many noncritical paths are pruned early, making pin-to-pin critical path analysis of large circuits feasible. It is demonstrated that a design methodology based on logic extraction, VHDL, and a layout tool can provide a fabricated functionally- correct IC design without circuit-level or switch-level simulation. This methodology is shown to be practical for VLSI …

Robotic Tactile Sensors Fabricated From A Monolithic Silicon Integrated Circuit And A Piezoelectric Polyvinylidene Fluoride Thin Film, Craig S. Dyson

Theses and Dissertations

The purpose of this research effort was to design, fabricate, and test a tactile sensor system consisting of an external high impedance switch circuit, an external multiplexing circuit, and a tactile sensor IC. In order to accomplish this objective, a hardware design and selection process was implemented along with a logical test methodology. An external multiplexer circuit samples all of the array elements in 50 ms. The current prototype sensor has linearity spanning loads of 0.8 g to 135 g, a load resolution of 20 g, and a maximum bandwidth of 25 Hz. Using an elementary shape recognition algorithm the …

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 …