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Bio-Inspired Self-Organizing Robotic Systems / edited by Yan Meng, Yaochu Jin.

By: Meng, Yan [editor.]Contributor(s): Jin, Yaochu [editor.] | SpringerLink (Online service)Material type: Text

TextSeries: Studies in Computational Intelligence: 355ISBN: 9783642207594Subject(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Robotics and Automation | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 629.892 LOC classification: Q342Online resources: Full text available from SpringerLink ebooks - Engineering (2011)

Contents:

Part I: Self-Organizing Swarm Robotic Systems -- Part II: Self-Reconfigurable Modular Robots -- Part III: Autonomous Mental Development in Robotic Systems -- Part IV: Special Applications Part III: Autonomous Mental Development in Robotic Systems -- Part IV: Special Applications.

In: Springer eBooksSpringerLink ebooks - Engineering (2011)Summary: 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.

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Item type	Current location	Home library	Shelving location	Call number	Status	Date due	Barcode	Item holds
Book	School of Mechanical & Manufacturing Engineering (SMME)	School of Mechanical & Manufacturing Engineering (SMME)	General Stacks	629.892 BIO (Browse shelf)	Available		SMME-1916

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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.

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