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Making Robots Smarter

Combining Sensing and Action Through Robot Learning

  • Katharina Morik
  • Michael Kaiser
  • Volker Klingspor

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Learning in Execution and Control

    1. Front Matter
      Pages 1-1
    2. M. Kaiser, R. Dillmann
      Pages 3-16
    3. C. Baroglio, A. Giordana, R. Piola
      Pages 17-44
    4. M. Nuttin, H. Van Brussel
      Pages 45-52
    5. M. Nuttin, H. Van Brussel
      Pages 53-64
    6. R. Suárez, L. Basañez, J. Rosell
      Pages 65-84
    7. J. del R. Millán, C. Torras
      Pages 85-107
  3. Learning for Human-Robot Interaction

    1. Front Matter
      Pages 127-127
    2. M. Kaiser, H. Friedrich, V. Klingspor, K. Morik
      Pages 129-136
    3. T. Rauber, M. Barata
      Pages 137-160
    4. L. Seabra Lopes, L. Camarinha-Matos
      Pages 161-184
    5. K. Morik, S. Wessel
      Pages 185-198
    6. V. Klingspor, K. Morik
      Pages 199-224
    7. A. Rieger, V. Klingspor
      Pages 225-240
  4. Back Matter
    Pages 241-271

About this book

Introduction

Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is the central issue. In the first part of the book, aspects of learning in execution and control are discussed. Methods for the automatic synthesis of controllers, for active sensing, for learning to enhance assembly, and for learning sensor-based navigation are presented. Since robots are not isolated but should serve us, the second part of the book discusses learning for human-robot interaction. Methods of learning understandable concepts for assembly, monitoring, and navigation are described as well as optimizing the implementation of such understandable concepts for a robot's real-time performance.
In terms of the study of embodied intelligence, Making Robots Smarter asks how skills are acquired and where capabilities of execution and control come from. Can they be learned from examples or experience? What is the role of communication in the learning procedure? Whether we name it one way or the other, the methodological challenge is that of integrating learning capabilities into robots.

Keywords

Navigation communication intelligence learning optimization robot sensing

Editors and affiliations

  • Katharina Morik
    • 1
  • Michael Kaiser
    • 2
  • Volker Klingspor
    • 3
  1. 1.Universität DortmundDortmundGermany
  2. 2.ABB Turbosystems AGBadenSwitzerland
  3. 3.SerCon — IBM Deutschland GmbHDortmundGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-5239-0
  • Copyright Information Kluwer Academic Publisher, Boston 1999
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7388-9
  • Online ISBN 978-1-4615-5239-0
  • Buy this book on publisher's site