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Studies in Systems, Decision and Control

Handling Uncertainty and Networked Structure in Robot Control

Editors: Busoniu, Lucian, Tamás, Levente (Eds.)

  • Presents in-depth coverage of a range of algorithms, which readers can implement and modify for their own systems
  • Demonstrates practical investigations and case studies that highlight the applicability of the techniques
  • Describes a selection of modern methods, offering readers up-to-date means of tackling uncertainty and network structure in robot control
  • Provides additional electronic material, such as source code and experimental data
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Buy this book

eBook 118,99 €
price for India (gross)
  • ISBN 978-3-319-26327-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 149,99 €
price for India (gross)
  • ISBN 978-3-319-26325-0
  • with online files
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover 149,99 €
price for India (gross)
  • ISBN 978-3-319-79932-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

About the authors

Lucian Busoniu received the M.Sc. degree (valedictorian) from the Technical University of Cluj-Napoca, Romania, in 2003 and the Ph.D. degree (cum laude) from the Delft University of Technology, the Netherlands, in 2009. He has held research positions in the Netherlands and France, and is currently an associate professor with the Department of Automation at the Technical University of Cluj-Napoca. His fundamental interests include planning-based methods for nonlinear optimal control, reinforcement learning and dynamic programming with function approximation, and multiagent systems; while his practical focus is applying these techniques to robotics. He has coauthored a book and more than 50 papers and book chapters on these topics. He was the recipient of the 2009 Andrew P. Sage Award for the best paper in the IEEE Transactions on Systems, Man, and Cybernetics. 

Levente Tamas received the M.Sc. (valedictorian) and the Ph.D. degree in electrical engineering from Technical University of Cluj-Napoca, Romania, in 2005 and 2010, respectively. He took part in several postdoctoral programs dealing with 3D perception and robotics, the most recent one spent at the Bern University of Applied Sciences, Switzerland. He is currently with the Department of Automation, Technical University of Cluj-Napoca, Romania. His research focuses on 3D perception and planning for autonomous mobile robots, and has resulted in several well ranked conference papers, journal articles, and book chapters in this field.

Table of contents (15 chapters)

  • Robot Learning for Persistent Autonomy

    Kormushev, Petar (et al.)

    Pages 3-28

    Preview Buy Chapter 24,95 €
  • The Explore–Exploit Dilemma in Nonstationary Decision Making under Uncertainty

    Axelrod, Allan (et al.)

    Pages 29-52

    Preview Buy Chapter 24,95 €
  • Learning Complex Behaviors via Sequential Composition and Passivity-Based Control

    Lopes, Gabriel A. D. (et al.)

    Pages 53-74

    Preview Buy Chapter 24,95 €
  • Visuospatial Skill Learning

    Ahmadzadeh, Seyed Reza (et al.)

    Pages 75-99

    Preview Buy Chapter 24,95 €
  • Observer Design for Robotic Systems via Takagi–Sugeno Models and Linear Matrix Inequalities

    Estrada-Manzo, Víctor (et al.)

    Pages 103-128

    Preview Buy Chapter 24,95 €

Buy this book

eBook 118,99 €
price for India (gross)
  • ISBN 978-3-319-26327-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 149,99 €
price for India (gross)
  • ISBN 978-3-319-26325-0
  • with online files
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover 149,99 €
price for India (gross)
  • ISBN 978-3-319-79932-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Handling Uncertainty and Networked Structure in Robot Control
Editors
  • Lucian Busoniu
  • Levente Tamás
Series Title
Studies in Systems, Decision and Control
Series Volume
42
Copyright
2015
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-26327-4
DOI
10.1007/978-3-319-26327-4
Hardcover ISBN
978-3-319-26325-0
Softcover ISBN
978-3-319-79932-2
Series ISSN
2198-4182
Edition Number
1
Number of Pages
XXVIII, 388
Number of Illustrations
26 b/w illustrations, 146 illustrations in colour
Topics