Bio-Inspired Self-Organizing Robotic Systems. Este artículo no está disponible.
Idioma: inglés
Editorial: Springer, 2011
Serie: Libro 26 de 538 - Studies in Computational Intelligence
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- Título
- Bio-Inspired Self-Organizing Robotic Systems
- Autor
- Meng, Yan (EDT); Jin, Yaochu (EDT)
- Editorial
- Springer
- Año de publicación
- 2011
- Estado
- As New
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 3642207596
- ISBN 13
- 9783642207594
- Serie
- Libro 26 de 538: 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.
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De la contraportada
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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