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

Por: Meng, Yan [editor.]Colaborador(es): Jin, Yaochu [editor.]Tipo de material: TextoTextoSeries Studies in Computational Intelligence, 355Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: X, 275 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642207600Trabajos contenidos: SpringerLink (Online service)Tema(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Robotics and Automation | Artificial Intelligence (incl. Robotics)Formatos físicos adicionales: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: de clik aquí para ver el libro electrónico
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Springer eBooksResumen: 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. ǣBio-inspired Self-organizing Robotic Systemsǥ 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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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.

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. ǣBio-inspired Self-organizing Robotic Systemsǥ 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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