Knowledge-Based Vision-Guided Robots

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1 Knowledge-Based Vision-Guided Robots

2 Studies in Fuzziness and Soft Computing Editor-in-chief Prof. Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences ul. Newelska Warsaw, Poland kacprzyk@ibspan.waw.pl = 2941 Further volumes of this series can be found at our homepage. Vol. 83. S. Barro and R. Marin (Eds.) Fuzzy Logic in Medicine. ISBN Vol. 84. L. C. Jain and J. Kacprzyk (Eds.) New Learning Paradigms in Soft Computing, ISBN Vol. 85. D. Rutkowska Neuro-Fuzzy Architectures and Hybrid Learning. ISBN Vol. 86. M. B. Gorzalczany Computational Intelligence Systems and Applications. ISBN Vol. 87. C. Bertoluzza, M. A. Gil and D. A. Ralescu (Eds.) Statistical Modeling, Analysis and Management of' Fuzzy Data, ISBN Vol. 88. R. P. Srivastava and T. J. Mock (Eds.) Belief Functions in Business Decisions, ISBN Vol. 89. B. Bouchon-Meunier, J. Gutierrez-Rios, L. Magdalena and R.R. Yager (Eds.) Technologies for Constructing Intelligent Systems I, ISBN Vol. 90. B. Bouchon-Meunier, J, Gutierrez-Rios, L. Magdalena and R.R. Yager (Eds.) Technologies for Constructing Intelligent Systems 2, ISBN Vol. 91. J.J. Buckley, E. Eslami and T. Feuring Fuzzy Mathematics in Economics and EnRineering, ISBN Vol. 92. P. P. Angelov Evolving Rule-Based Models, ISBN Vol. 93. V. V. Cross and T. A. Sudkamp Similarity and Compatibility in Fuzzy Set Theory, ISBN X Vol. 94. M. MacCrimmon and P. Tillers (Eds.) The Dynamics of Judicial Proof', ISBN Vol. 95. T. Y. Lin. Y. Y. Yao and L. A. Zadeh (Eds.) Data Mining, Rough Sets and Granular Computing, ISBN X Vol. 96. M. Schmitt, H.-N. Teodorescu, A. Jain, A. Jain, S. Jain and L. C. Jain (Eds.) Computational Intelligence Processing in Medical Diagnosis, ISBN Vol. 97. T. Calvo, G. Mayor and R. Mesiar (Eds.) Aggregation Operators, ISBN Vol. 98. L. C. Jain, Z. Chen and N. Ichalkaranje (Eds.) Intelligent Agents and Their Applications, ISBN Vol. 99. C. Huang and Y. Shi Towards Efficient Fuzzy Information Processing, ISBN X Vol S.-H. Chen (Ed.) Evolutionary Computation in Economics and Finance, ISBN Vol S. J. Ovaska and L. M. Sztandera (Eds.) Soft Computing in Industrial Electronics, ISBN Vol B. Liu Theory and Praxis of Uncertain Programming, ISBN

3 Nick Barnes Zhi-Qiang Liu Knowledge-Based Vision-Guided Robots With 99 Figures and 3 Tables Physica-Verlag A Springer-Verlag Company

4 Dr. Nick Barnes University of Melbourne Department of Computer Science and Software Engineering 3010 Victoria Australia Professor Zhi-Qiang Liu City University of Hong-Kong School of Creative Media Tat Chee Ave., Kowloon Hong Kong P. R. China ISSN ISBN Library of Congress Cataloging-in-Publication Data applied for Die Deutsche Bibliothek - CIP-Einheitsaufnahme Barnes, Nick: Knowledge based vision guided robots: with 3 tables / Nick Barnes; Zhi-Qiang Liu. - Heidelberg; New York: Physica-VerI., (Studies in fuzziness and soft computing; Vol. 103) ISBN ISBN (ebook) DOI / This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Physica-Verlag. Violations are liable for prosecution under the German Copyright Law. Physica-Verlag Heidelberg New York a member of BertelsmannSpringer Science+Business Media GmbH Physica-Verlag Heidelberg Softcover reprint of the hardcover 1 st edition The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Hardcover Design: Erich Kirchner, Heidelberg SPIN / I 0 - Printed on acid-free paper

5 Acknow ledgements The authors would like to thank members of technical services of the department, particularly, John Horvath, Andrew Peel, Thomas Weichert, and David Hornsby, for keeping robots and cameras going, despite our best efforts to burn, crash, and destroy them in anyway possible. Nick Barnes would also like to thank Andrew Howard, Sandy Dance, and Les Kitchen for the challenging research discussions. Thank-you to my family, Betty, Barry, Lisa and Dale for supporting me in this strange enterprise called research. Also, my other family John and Wendy for support, encouragement and Sunday dinners. Finally to Nina, the greatest person whom I know. Her inspiration is a great source of strength to me. Her support of everything that I do makes challenges seem easy. Her company makes problems seem trivial. Her smile makes everything else seem unimportant. Her writing and editing skills have improved this book beyond recognition. Without her help this book would never be completed.

6 ... if there were machines which bore a resemblance to our body and imitated our actions as far as it was morally possible to do so, we should always have two very certain tests by which to recognise that, for all that, they were not real men. R. Descarte. circa [95]1 I possessed the capacity of bestowing animation, yet to prepare a frame for the reception of it, with all its intricacies of fibres, muscles, and veins, still remained a work of inconceivable difficulty and labour. Frankenstein. Mary Shelley, [201]... to manufacture artificial workers is the same thing as to manufacture motors. The process must be of the simplest, and the product of the best from a practical point of view. R. U. R. (Rossum's Universal Robots). (English translation) Karel Capek, [39] lsee conclusion full text.

7 Contents 1 Introduction Background A vision-guided approach Computer vision and vision-guided mobile robots Applying high-level computer vision to guide mobile robots Aims of the Research Presented in this Book: A Problem in Robot Vision The Approach of this Book About the Chapters 7 2 Related Systems and Ideas Basic computer vision approaches Frame-based computer vision Active vision Vision-Guided Mobile Robot Systems Mobile robot subsystems and concepts Mobile robot object recognition Maps and path planning Temporal sequencing for complex tasks Vision-guided mobile robot systems Reactive navigation Model-based vision systems for mobile robots Knowledge-based mobile robotic systems Vision-guided mobile robots using stereo Active perception systems for mobile robots Application of vision-guided mobile robots Computer Vision for Mobile Robots 31

8 x Contents Traditional model-based vision 3D object recognition Shape-from-shading Pose determination. 2.4 Conclusion Embodied Vision For Mobile Robots! Introduction Embodiment Phenomena and noumena The Classical Computer Vision Paradigm Non-classical computer vision Problems with Classical Computer Vision Applying Embodied Concepts in Human Vision Models play an analogous role in computer vision Embodiment of Vision-guided Robots Embodiment, task and environment The role of the task The role of the environment Embodiment for Vision-guided Robots Physical embodiment Embodiment in a task Embodiment in an environment. 3.7 Conclusion Object Recognition Mobile Robot Guidance Introduction System Perspective Object Recognition Canonical-views Match verification Edge matching Edge-based features for ground-based robots View prediction Determining Object Pose and Distance Active determination of the sign of (J Error analysis. 4.5 Conclusion

9 Contents XI 5 Edge Segmentation and Matching 5.1 Edge Extraction Edge extraction On the choice of window size and quantisation of p and e Edge Matching Evaluating matches Spatial elimination. Edge coverage.... Position estimation consistency Geometric verification.. Quadratic edge extraction Further active processing Knowledge Based Shape from Shading Introduction Motivation and system perspective Assumptions Knowledge-based representation of objects Using Object Model Knowledge for Shape-From-Shading A New Boundary Condition for Shape-From-Shading Knowledge-based Implementation Knowledge / frame topology Fact knowledge Procedural knowledge Shape processing rulebase Experimental Method and Results Synthetic images Real images Domain knowledge 6.6 Conclusion Supporting Navigation Components Model-based Path Planning Path planning and obstacle avoidance Odometry and Obstacle Avoidance Subsystem Obstacle avoidance strategies Coordinate transforms

10 XII Contents 8 Fuzzy Control for Active Perceptual Docking Introduction Fuzzy control Fuzzy control for mobile robot control TSK fuzzy model Visual motion-based approaches to mobile robots and the docking problem Direction Control for Robot Docking The log-polar camera Docking for a ground-based robot Noise in the input parameter A Fuzzy Control Scheme Results Conclusion System Results and Case Studies Evaluation of Components Experimental setup View matching Pose determination - power supply Pose determination - model vehicle Case Studies Moving around the corner of an object Distinguishing a particular object among similar objects Docking Object circumnavigation Obstacle avoidance Conclusion Conclusion Limitations of the Research Presented and Future Work Extended quotation from Descartes Index 231

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