
Obstacle Avoidance In Multi-robot Systems, Experiments In Parallel Genetic Algorithms
World Scientific Publishing Co Pte Ltd
Will be published approx. on 19. June 1998
Book
Hardback
200 pages
978-981-02-3423-2 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 224 mm
Width: 161 mm
Thickness: 17 mm
Weight
408 gr
ISBN-13
978-981-02-3423-2 (9789810234232)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Author
University Of Western Australia, Australia
University Of Sydney, Australia
Content
Overview; parallel computing; path planning; search techniques; inverse kinematics; collision detection; collision avoidance; examples; discussion, conclusions and future work.