Bio-Inspired Self-Organizing Robotic Systems

  • Yan Meng
  • Yaochu Jin
Part of the Studies in Computational Intelligence book series (SCI, volume 355)

Table of contents

  1. Front Matter
  2. Self-Organizing Swarm Robotic Systems

  3. Self-Reconfigurable Modular Robots

    1. Front Matter
      Pages 121-121
    2. Serge Kernbach, Benjamin Girault, Olga Kernbach
      Pages 123-141
    3. Yan Meng, Yaochu Jin
      Pages 143-171
    4. Shuhei Miyashita, Aubery Marchel Tientcheu Ngouabeu, Rudolf M. Füchslin, Kohei Nakajima, Christof Audretsch, Rolf Pfeifer
      Pages 173-191
  4. Autonomous Mental Development in Robotic Systems

    1. Front Matter
      Pages 193-193
    2. Juyang Weng
      Pages 195-212
  5. Special Applications

    1. Front Matter
      Pages 213-213
    2. Jeff Jones, Soichiro Tsuda, Andrew Adamatzky
      Pages 215-251
    3. Alwin Hoffmann, Florian Nafz, Andreas Schierl, Hella Seebach, Wolfgang Reif
      Pages 253-273
  6. Back Matter

About this book

Introduction

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.

 

Keywords

Robotics Self-organizing robotic systems bio-inspired robotic systems

Editors and affiliations

  • Yan Meng
    • 1
  • Yaochu Jin
    • 2
  1. 1.Department of Electrical and Computer EngineeringStevens Institute of TechnologyHobokenUSA
  2. 2.Department of ComputingUniversity of SurreyGuildfordUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-20760-0
  • Copyright Information Springer Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-20759-4
  • Online ISBN 978-3-642-20760-0
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book