Bio-Inspired Self-Organizing Robotic Systems

2011
ISBN: 978-3-642-20759-4
Verlag: Springer

Buch, Englisch, Band 355, 275 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 653 g

Reihe: Studies in Computational Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Jin, Yaochu

Meng, Yan

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Technische Wissenschaften Technik Allgemein Bionik, Biomimetik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Part I:  Self-Organizing Swarm Robotic Systems

 

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Part II: Self-Reconfigurable Modular Robots

 

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Part III: Autonomous Mental Development in Robotic Systems

 

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Part IV:  Special Applications

 

Part III: Autonomous Mental Development in Robotic Systems

 

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Part IV:  Special Applications.