Bio-Inspired Self-Organizing Robotic Systems
Editors: Meng, Yan, Jin, Yaochu (Eds.)
Free Preview- State-of-the-art research inspired by biological principles for self-organizing robotic systems
- Bridges multi-disciplinary research areas such as robotics, artificial life, systems biology, and evolutionary computation
- Written by experts in the field
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- About this book
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Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments. Compared with classical control methods for robotic systems, the major advantages of bio-inspired self-organizing robotic systems include robustness, self-repair and self-healing in the presence of system failures and/or malfunctions, high adaptability to environmental changes, and autonomous self-organization and self-reconfiguration without a centralized control. “Bio-inspired Self-organizing Robotic Systems” provides a valuable reference for scientists, practitioners and research students working on developing control algorithms for self-organizing engineered collective systems, such as swarm robotic systems, self-reconfigurable modular robots, smart material based robotic devices, unmanned aerial vehicles, and satellite constellations.
- Table of contents (11 chapters)
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Morphogenetic Robotics - An Evolutionary Developmental Approach to Morphological and Neural Self-Organization of Robotic Systems
Pages 3-23
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How to Engineer Robotic Organisms and Swarms?
Pages 25-52
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Flocking Control Algorithms for Multiple Agents in Cluttered and Noisy Environments
Pages 53-79
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Genetic Stigmergy
Pages 81-103
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From Ants to Robots and Back: How Robotics Can Contribute to the Study of Collective Animal Behavior
Pages 105-120
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Table of contents (11 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Bio-Inspired Self-Organizing Robotic Systems
- Editors
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- Yan Meng
- Yaochu Jin
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 355
- Copyright
- 2011
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer Berlin Heidelberg
- eBook ISBN
- 978-3-642-20760-0
- DOI
- 10.1007/978-3-642-20760-0
- Hardcover ISBN
- 978-3-642-20759-4
- Softcover ISBN
- 978-3-662-50664-6
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- X, 275
- Topics
