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IEEE International Conference on systems, Man and Cybernetics

作者： E. Tunstel NASA Jet Propulsion Laboratory USA CAD Laboratory for Intelligent & Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

Mobile robot navigation can be achieved using a control system comprised of a collection of special-purpose motion routines, or behaviors. In order to exhibit robust autonomous performance, a suitable strategy for coordinating the behaviors must be adopted. This paper describes an approach to behavior coordination and conflict resolution within the context of a hierarchical architecture of fuzzy behaviors. This architecture can be viewed as a network of distributed intelligent behaviors in which coordination is achieved using weighted decision-making based on behavioral degrees of applicability. Aspects of the coordination and conflict resolution procedures that are based on generalized concepts from fuzzy control are discussed. The strategy is appropriate for fuzzy control of systems that can be represented by hierarchical or decentralized structures.

关键词： Fuzzy control Mobile robots Robot control Control systems intelligent robots Fuzzy systems intelligent systems Decision making Automatic control Laboratories

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TMS320 DSP based neuro-fuzzy controller

TMS320 DSP based neuro-fuzzy controller

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IEEE International Conference on systems, Man and Cybernetics

作者： K.K. Kumbla M.-R. Akbarzadeh-T. M. Jamshidi CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA University of New Mexico Albuquerque NM US CAD Lab. for Intelligent & Robotic Syst. New Mexico Univ. Albuquerque NM USA

Fuzzy logic can be used to map complex nonlinear relations by a set of IF-THEN rules. The membership functions are designed by intuitive human reasoning. This poses two problems; first, for different control application a new set of membership functions have to developed and second, once these membership functions are developed and implemented there is no means of changing them. This means fuzzy logic lacks a learning function. Neural network on the other hand self-organizes the mapping relationship by learning. So by integrating neural networks and fuzzy logic it is possible to overcome these problems. Implementing this algorithm on a TMS320 DSP chip is discussed. Controlling a flexible link manipulator is taken as an example to evaluate the controller.

关键词： Digital signal processing Fuzzy logic Biological neural networks Artificial neural networks Fuzzy reasoning Neural networks Humans Fuzzy set theory Fuzzy control Fuzzy neural networks

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FUZZY-LOGIC BASED COLLISION-AVOIDANCE FOR A MOBILE ROBOT

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roboticA 1994年第6期12卷 521-527页

作者： MARTINEZ, A TUNSTEL, E JAMSHIDI, M CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM 87131 (USA)

Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the priority. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem. The fuzzy controller was tested on a mobile robot system in an indoor environment and found to perform satisfactorily despite having crude sensors and minimal sensory feedback.

关键词： FUZZY LOGIC COLLISION AVOIDANCE MOBILE ROBOT NAVIGATION

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A truth qualified fuzzy logic rule based expert system with application to image enhancement

A truth qualified fuzzy logic rule based expert system with ...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： A. Asgharzadeh M. Jamshidi N. Vadiee CAD Laboratory for Intelligent and Robotic Systems EECE Department University of New Mexico Albuquerque NM USA

The development and analysis of a qualified fuzzy logic rule based expert system capable of enhancing the quality of printed image is introduced in this paper. This is achieved by using qualifiers and quantifiers in expressing the rule base to control image attributes such as color, tint, contrast, brightness, and sharpness. To develop the rule based system, a set of experiments are conducted to extract the knowledge of the experts. This is achieved by allowing each expert to obtain a set of prints for each image in a test set. Each print is given a score (S) by human experts. From this result a set of quantified fuzzy IF-THEN rules are derived to maximize score S over a large set of printed pictures.< >

关键词： Fuzzy logic Expert systems Image enhancement Humans Control systems Hybrid intelligent systems Uncertainty Printers intelligent robots Fuzzy sets

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TELEroboticS AND MOBILE ROBOTS FOR SPACE APPLICATIONS - INTRODUCTION

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roboticA 1994年第6期12卷 479-479页

作者： JAMSHIDI, M CAD Laboratory for Intelligent & Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM87131 (USA)

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A hierarchical fuzzy controller using line-curvature feature extraction for a single link flexible arm

A hierarchical fuzzy controller using line-curvature feature...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： M.-R. Akbarzadeh-Totonchi M. Jamshidi N. Vadiee CAD For Intelligent and Robotic Systems Laboratory Department of Electrical Engineering and Computer Engineering University of New Mexico Albuquerque NM USA

A two-level hierarchical fuzzy controller is developed for a single flexible link. The second level of hierarchy monitors the behavior of the robot arm and extracts features such as straight, oscillatory, gently curved. This is accomplished using a fuzzy feature extraction technique which incorporates line-curvature data computed over a finite number of discrete points along the length of the robot arm. The line-curvature data are computed from measurements of a finite number of strain sensors. The fuzzy features such as straight, oscillatory, gently curved, the angular position measurements of the tip of the robot arm, and the torque of the motor constitute a basis of information for the first level of the hierarchical fuzzy controller.< >

关键词： Fuzzy control Feature extraction Robot control Service robots Fuzzy systems Control systems intelligent robots Data mining Robot sensing systems Strain measurement

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Fuzzy logic and behavior control strategy for autonomous mobile robot mapping

Fuzzy logic and behavior control strategy for autonomous mob...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： E. Tunstel M. Jamshidi NASA Jet Propulsion Laboratory Pasadena CA USA CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

In support of research efforts to develop reactive mobile robots capable of autonomous navigation, we are concentrating on providing human reasoning capabilities as a resource for intelligence and integrating the world mapping and navigation tasks. The underlying philosophy is that an autonomous mobile robot should be able to make a map of its environment as it navigates through that environment. Fuzzy logic control and behavior-based navigation are proposed as means to implement this philosophy. Fuzzy logic provides the approximate reasoning necessary for handling the uncertainty inherent in mobile robot navigation. By decomposing the problem into simpler tasks we can develop mobile robots that exhibit a sufficient level of intelligence for performing navigation and mapping. In this paper, we discuss a strategy for incorporating fuzzy reasoning into the framework of reactive behavior control systems for autonomous mapping.< >

关键词： Fuzzy logic Mobile robots Navigation Control systems intelligent robots intelligent systems intelligent sensors Motion control Laboratories Uncertainty

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Fuzzy logic based collision avoidance for a mobile robot 3

Fuzzy logic based collision avoidance for a mobile robot

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3rd International Conference on Industrial Fuzzy Control and intelligent systems, IFIS 1993

作者： Martinez, A. Tunstel, E. Jamshidi, M. CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States NASA Jet Propulsion Laboratory PasadenaCA United States

ISBN: (纸本)0780314859

Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the proirity. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem. © 1993 IEEE.

关键词： Collision avoidance

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Real-Time Fuzzy Control of Electric Power systems

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IFAC Proceedings Volumes 1993年第2期26卷 745-748页

作者： E. Kristjánsson D. Barak M. Jamshidi CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM 87131 USA

In this paper, the application of a real-time fuzzy controller is presented in order to improve the power system stability. The above is done with the means of the fuzzy membership functions whose values are computed depending on the measured generator frequency and voltage. The controller was tested in real time for different loads on the generator. For comparison a proportional crisp controller was also design and tested under the same circumstances.

关键词： Power System Stabilizer Fuzzy Control Real Time Control Power Sytems

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A Simulation Environment for Fuzzy Control of Traffic systems

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IFAC Proceedings Volumes 1993年第2期26卷 753-756页

作者： R. Kelsey K. Bisset M. Jamshidi Los Alamos National Laboratory Los Alamos NM 87545 USA CAD Laboratory for Intelligent and Robotic Systems Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM 87131 USA

In this paper fuzzy control and decision making are used to simulate the control of traffic flow at an intersection. Fuzzy logic can be used as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller a computer simulation is constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. The fuzzy logic controller proved to be a better method of control than conventional control methods, especially in the case of highly uneven traffic flow between different directions

关键词： Fuzzy logic fuzzy control traffic control simulation

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