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Fuzzy Logic Techniques for Autonomous Vehicle Navigation

  • Book
  • © 2001

Overview

Editors:
  1. Dimiter Driankov

    1. Department of Technology, Örebro University, Örebro, Sweden

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  2. Alessandro Saffiotti

    1. Department of Technology, Örebro University, Örebro, Sweden

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  • Presentation of state-of-the art fuzzy logic techniques used to solve the major problems in autonomous robot navigation
  • Reproducibility of proposed solutions by the reader
  • Discussion of pros and cons of using fuzzy logic techniques on the basis of extensive experimentation on real mobile robots

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 61)

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Table of contents (15 chapters)

  1. Front Matter

    Pages I-VIII
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  2. Tutorials

    1. Front Matter

      Pages 1-1
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    2. Fuzzy Logic in Autonomous Navigation

      • Alessandro Saffiotti
      Pages 3-24

    3. A Reminder on Fuzzy Logic

      • Dimiter Driankov
      Pages 25-47

  3. Design of Individual Behaviors

    1. Front Matter

      Pages 49-49
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    2. Mobile Robot Path Tracking and Visual Target Tracking Using Fuzzy Logic

      • Annibal Ollero, Joaquin Ferruz, Omar Sánchez, Guillermo Heredia
      Pages 51-72

    3. Fuzzy Logic for Fusion of Tactical Influences on Vehicle Speed Control

      • Robin R. Murphy
      Pages 73-96

    4. Neuro-Fuzzy Control for Basic Mobile Robot Behaviours

      • Jelena Godjevac, Nigel Steele
      Pages 97-117

    5. The Role of Fuzzy Logic Control in Evolutionary Robotics

      • Frank Hoffmann
      Pages 119-147

  4. Coordination of Behavior

    1. Front Matter

      Pages 149-149
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    2. Resolving Conflicts Between Behaviors Using Suppression and Inhibition

      • François G. Pin, Yutaka Watanabe
      Pages 151-178

    3. Multi-Layered Fuzzy Behavior Fusion for Reactive Control of Autonomous Robots

      • Steven G. Goodridge, Michael G. Kay
      Pages 179-203

    4. Fuzzy-Behavior Synthesis, Coordination, and Evolution in an Adaptive Behavior Hierarchy

      • Edward W. Tunstel Jr.
      Pages 205-234

    5. Multiple Objective vs. Fuzzy Behavior Coordination

      • Paolo Pirjanian, Maja Matarić
      Pages 235-253

  5. Mapping the Environment

    1. Front Matter

      Pages 255-255
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    2. Accurate Map Building via Fusion of Laser and Ultrasonic Range Measures

      • Elisabetta Fabrizi, Giuseppe Oriolo, Giovanni Ulivi
      Pages 257-279

    3. Map Generation by Co-operative Autonomous Robots Using Possibility Theory

      • Maite López-Sánchez, Ramon López de Màntaras, Carles Sierra
      Pages 281-312

    4. Integrating Linguistic Descriptions and Sensor Observations for the Navigation of Autonomous Robots

      • Jorge Gasós
      Pages 313-339

  6. Layer Integration

    1. Front Matter

      Pages 341-341
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    2. MORIA: A Robot with Fuzzy Controlled Behaviour

      • Hartmut Surmann, Liliane Peters
      Pages 343-365
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Keywords

About this book

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.

Editors and Affiliations

  • Department of Technology, Örebro University, Örebro, Sweden

    Dimiter Driankov, Alessandro Saffiotti

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