Handling Uncertainty and Networked Structure in Robot Control

  • Lucian Busoniu
  • Levente Tamás

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 42)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Learning Control in Unknown Environments

    1. Front Matter
      Pages 1-1
    2. Petar Kormushev, Seyed Reza Ahmadzadeh
      Pages 3-28
    3. Gabriel A. D. Lopes, Esmaeil Najafi, Subramanya P. Nageshrao, Robert Babuška
      Pages 53-74
    4. Seyed Reza Ahmadzadeh, Petar Kormushev
      Pages 75-99
  3. Dealing with Sensing Uncertainty

    1. Front Matter
      Pages 101-101
    2. Víctor Estrada-Manzo, Zsófia Lendek, Thierry-Marie Guerra
      Pages 103-128
    3. Robert Frohlich, Levente Tamás, Zoltan Kato
      Pages 129-151
    4. Michael Beetz, Ferenc Bálint-Benczédi, Nico Blodow, Christian Kerl, Zoltán-Csaba Márton, Daniel Nyga et al.
      Pages 181-208
    5. Henry Carrillo, José A. Castellanos
      Pages 209-235
    6. Karol Hausman, Dejan Pangercic, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Christian Bersch, Megha Gupta et al.
      Pages 237-262
  4. Control of Networked and Interconnected Robots

    1. Front Matter
      Pages 263-263
    2. Előd Páll, Levente Tamás, Lucian Buşoniu
      Pages 265-290
    3. Piroska Haller, Lőrinc Márton, Zoltán Szántó, Tamás Vajda
      Pages 291-311
    4. Marcos Cesar Bragagnolo, Irinel-Constantin Morărescu, Lucian Buşoniu, Pierre Riedinger
      Pages 313-333
    5. Haci M. Guzey, Travis Dierks, Sarangapani Jagannathan
      Pages 335-360
    6. Amélie Chevalier, Cosmin Copot, Robin De Keyser, Andres Hernandez, Clara Ionescu
      Pages 361-386
  5. Back Matter
    Pages 387-388

About this book

Introduction

This book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describes learning control to address environmental uncertainty. Part II discusses state estimation, active sensing, and complex scenario perception to tackle sensing uncertainty. Part III completes the book with control of networked robots and multi-robot teams.

Each chapter features in-depth technical coverage and case studies highlighting the applicability of the techniques, with real robots or in simulation. Platforms include mobile ground, aerial, and underwater robots, as well as humanoid robots and robot arms. Source code and experimental data are available at http://extras.springer.com.

The text gathers contributions from academic and industry experts, and offers a valuable resource for researchers or graduate students in robot control and perception. It also benefits researchers in related areas, such as computer vision, nonlinear and learning control, and multi-agent systems.

Keywords

Autonomous Mobile Robots Learning-based Control Networked Multi-robot Systems Networked Single-robot Systems Perception in Complex Systems State Estimation

Editors and affiliations

  • Lucian Busoniu
    • 1
  • Levente Tamás
    • 2
  1. 1.Automation DepartmentTechnical University of Cluj-NapocaCluj-NapocaRomania
  2. 2.Automation DepartmentTechnical University of Cluj-NapocaCluj-NapocaRomania

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-26327-4
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-26325-0
  • Online ISBN 978-3-319-26327-4
  • Series Print ISSN 2198-4182
  • Series Online ISSN 2198-4190
  • About this book