Obstacle Avoidance In Multi-robot Systems, Experiments In Parallel Genetic Algorithms

By: Albert Y Zomaya, Mark A C Gill

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Hardcover | 19 June 1998

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200 Pages

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22.23 x 16.51 x 1.27

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Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path planning problem for robot manipulators. Simple and efficient solutions are proposed for the path planning problem based on genetic algorithms. One of the attractive features of genetic algorithms is their ability to solve formidable problems in a robust and straightforward manner. Moreover, genetic algorithms are inherently parallel in nature, which makes them ideal candidates for parallel computing implementations.By combining the robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexities involved in the development of parallel path planning algorithms. The material presented is interdisciplinary in nature — it combines topics from robotics, genetic algorithms, and parallel processing. The book can be used by practitioners and researchers in computer science and engineering.

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Preface
Abbreviations
Overview
Parallel Computing
Path Planning
Search Techniques
Inverse Kinematics
Collision Detection
Collision Avoidance
Examples
Discussion, Conclusions and Future Work
References
Parallel Line Proof
Polynomial Method
Index
Table of Contents provided by Blackwell. All Rights Reserved.

Obstacle Avoidance In Multi-robot Systems, Experiments In Parallel Genetic Algorithms

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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