Fuzzy Logic Techniques for Autonomous Vehicle Navigation
In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new­ comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: • Selecting contributions which are representative of a wide range of prob­ lems and solutions and which have been validated on real robots; and • Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.
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Fuzzy Logic Techniques for Autonomous Vehicle Navigation
In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new­ comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: • Selecting contributions which are representative of a wide range of prob­ lems and solutions and which have been validated on real robots; and • Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.
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Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Fuzzy Logic Techniques for Autonomous Vehicle Navigation

eBook2001 (2001)

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Overview

In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new­ comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: • Selecting contributions which are representative of a wide range of prob­ lems and solutions and which have been validated on real robots; and • Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.

Product Details

ISBN-13: 9783790818352
Publisher: Physica
Publication date: 03/09/2013
Series: Studies in Fuzziness and Soft Computing , #61
Sold by: Barnes & Noble
Format: eBook
File size: 14 MB
Note: This product may take a few minutes to download.

Table of Contents

I: Tutorials.- Fuzzy Logic in Autonomous Navigation.- A Reminder on Fuzzy Logic.- II: Design of Individual Behaviors.- Mobile Robot Path Tracking and Visual Target Tracking Using Fuzzy Logic.- Fuzzy Logic for Fusion of Tactical Influences on Vehicle Speed Control.- Neuro-Fuzzy Control for Basic Mobile Robot Behaviours.- The Role of Fuzzy Logic Control in Evolutionary Robotics.- III: Coordination of Behaviors.- Resolving Conflicts Between Behaviors Using Suppression and Inhibition.- Multi-Layered Fuzzy Behavior Fusion for Reactive Control of Autonomous Robots.- Fuzzy-Behavior Synthesis, Coordination, and Evolution in an Adaptive Behavior Hierarchy.- Multiple Objective vs. Fuzzy Behavior Coordination.- IV: Mapping the Environment.- Accurate Map Building via Fusion of Laser and Ultrasonic Range Measures.- Map Generation by Co-operative Autonomous Robots Using Possibility Theory.- Integrating Linguistic Descriptions and Sensor Observations for the Navigation of Autonomous Robots.- V: Layer Integration.- MORIA: A Robot with Fuzzy Controlled Behaviour.- Integrating Deliberative and Reactive Strategies via Fuzzy Modular Control.- List of Contributors.
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