Knowledge-based vision-guided

Nick Barnes, Zhi-Qiang Liu

234 pages, parution le 21/08/2002

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Résumé

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.

Contents

Introduction
Related systems and ideas
Embodied vision for mobile robots
Object recognition mobile robots guidance
Edge segmentation and matching
Knowledge based shape from shading
Supporting navigation components
Fuzzy control for active perceptual docking
System results and case studies
Conclusion

L'auteur - Nick Barnes

Barnes, N., University of Melbourne, Victoria, Australia;

L'auteur - Zhi-Qiang Liu

Liu, Z.-Q., City University of Hong Kong, China

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Nick Barnes, Zhi-Qiang Liu
Parution	21/08/2002
Nb. de pages	234
Format	16 x 24
Couverture	Relié
Poids	485g
Intérieur	Noir et Blanc
EAN13	9783790814941