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Knowledge-Based Vision-Guided Robots

  • Book
  • © 2002

Overview

Authors:
  1. Nick Barnes

    1. Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia

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  2. Zhi-Qiang Liu

    1. School of Creative Media, City University of Hong-Kong, Hong Kong, P. R. China

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 103)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XII
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  2. Introduction

    • Nick Barnes, Zhi-Qiang Liu
    Pages 1-8

  3. Related Systems and Ideas

    • Nick Barnes, Zhi-Qiang Liu
    Pages 9-43

  4. Embodied Vision For Mobile Robots

    • Nick Barnes, Zhi-Qiang Liu, Edwin Coleman
    Pages 45-62

  5. Object Recognition Mobile Robot Guidance

    • Nick Barnes, Zhi-Qiang Liu
    Pages 63-86

  6. Edge Segmentation and Matching

    • Nick Barnes, Zhi-Qiang Liu
    Pages 87-107

  7. Knowledge Based Shape from Shading

    • Nick Barnes, Zhi-Qiang Liu
    Pages 109-134

  8. Supporting Navigation Components

    • Nick Barnes, Zhi-Qiang Liu
    Pages 135-145

  9. Fuzzy Control for Active Perceptual Docking

    • Nick Barnes, Zhi-Qiang Liu
    Pages 147-164

  10. System Results and Case Studies

    • Nick Barnes, Zhi-Qiang Liu
    Pages 165-202

  11. Conclusion

    • Nick Barnes, Zhi-Qiang Liu
    Pages 203-207

  12. Back Matter

    Pages 209-234
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Keywords

About this book

Many robotics researchers consider high-level vision algorithms (computational) too expensive for use in robot guidance. This book introduces the reader to an alternative approach to perception for autonomous, mobile robots. It explores how to apply methods of high-level computer vision and fuzzy logic to the guidance and control of the mobile robot. The book introduces a knowledge-based approach to vision modeling for robot guidance, where advantage is taken of constraints of the robot's physical structure, the tasks it performs, and the environments it works in. This facilitates high-level computer vision algorithms such as object recognition at a speed that is sufficient for real-time navigation. The texts presents algorithms that exploit these constraints at all levels of vision, from image processing to model construction and matching, as well as shape recovery. These algorithms are demonstrated in the navigation of a wheeled mobile robot.

Authors and Affiliations

  • Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia

    Nick Barnes

  • School of Creative Media, City University of Hong-Kong, Hong Kong, P. R. China

    Zhi-Qiang Liu

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