Mobile Robots: The Evolutionary Approach

  • Nadia Nedjah
  • Leandro dos Santos Coelho
  • Luiza de Macedo Mourelle

Part of the Studies in Computational Intelligence book series (SCI, volume 50)

Table of contents

  1. Front Matter
    Pages I-XXI
  2. Evolutionary Mobile Robots

  3. Learning Mobile Robots

    1. Front Matter
      Pages 120-120
    2. Jindong Liu, Lynne E. Parker, Raj Madhavan
      Pages 121-135
    3. Esther L. Colombini, Carlos H. C. Ribeiro
      Pages 137-159
    4. Antonio Henrique Pinto Selvatici, Anna Helena Reali Costa
      Pages 161-184
    5. Yi Guo, Lynne E. Parker, Raj Madhavan
      Pages 185-200
    6. Dennis Barrios-Aranibar, Pablo Javier Alsina
      Pages 201-219
  4. Back Matter
    Pages 221-223

About this book

Introduction

The design and control of autonomous intelligent mobile robotic systems operating in unstructured changing environments includes many objective difficulties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to fit in their environments. The application and use of bio-inspired and intelligent techniques such as reinforcement learning, artificial neural networks, evolutionary computation and so forth in the design and improvement of robot designs is an emergent research topic. Researchers have obtained robots that display an amazing slew of behaviours and perform a multitude of tasks. These include perception of environment, planning and navigation in rough terrain, pushing boxes, negotiating an obstacle course, etc.

In this context, mobile robots designed using evolutionary computation approaches, usually known as Mobile Evolutionary Robotics, have experienced significant development in the last decade. The fundamental goal of mobile evolutionary robotics is to apply evolutionary computation methods to automate the production of complex behavioural robotic controllers.

This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.

Keywords

Navigation architecture autonomous robot behavior cognition evolution evolutionary computation fuzzy learning mobile robot perception reinforcement learning robot robotics rough terrain

Editors and affiliations

  • Nadia Nedjah
    • 1
  • Leandro dos Santos Coelho
    • 2
  • Luiza de Macedo Mourelle
    • 3
  1. 1.Faculdade de EngenhariaUniversidade do Estado do Rio de JaneiroMaracanãBrazil
  2. 2.Pontifical Catholic University of ParanáCuritibaBrazil
  3. 3.Faculdade de EngenhariaUniversidade do Estado do Rio de JaneiroMaracanãBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-49720-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-49719-6
  • Online ISBN 978-3-540-49720-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book