Amazon cover image
Image from Amazon.com

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

Contributor(s): Series: Studies in Computational Intelligence ; 355Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: X, 275 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642207600
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q342
Online resources:
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 eBooksSummary: 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.  .
Item type: eBooks
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

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. “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.  .

Copyright © 2020 Alfaisal University Library. All Rights Reserved.
Tel: +966 11 2158948 Fax: +966 11 2157910 Email:
librarian@alfaisal.edu