Advances in Plan-Based Control of Robotic Agents

International Seminar Dagstuhl Castle, Germany, October 21–26, 2001 Revised Papers

  • Michael Beetz
  • Joachim Hertzberg
  • Malik Ghallab
  • Martha E. Pollack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2466)

Table of contents

  1. Front Matter
    Pages I-VIII
  2. Rachid Alami, Silvia Silva da Costa Bothelho
    Pages 1-20
  3. Michael Beetz, Andreas Hofhauser
    Pages 21-35
  4. Sebastian Buck, Thorsten Schmitt, Michael Beetz
    Pages 36-51
  5. Wolfram Burgard, Mark Moors, Frank Schneider
    Pages 52-70
  6. Hans-Dieter Burkhard, Joscha Bach, Ralf Berger, Birger Brunswieck, Michael Gollin
    Pages 71-88
  7. Silvia Coradeschi, Alessandro Saffiotti
    Pages 89-105
  8. Lars Karlsson, Tommaso Schiavinotto
    Pages 106-122
  9. Khaled Ben Lamine, Froduald Kabanza
    Pages 123-139
  10. Maxim Likhachev, Sven Koenig
    Pages 140-156
  11. Benoit Morisset, Malik Ghallab
    Pages 157-178
  12. Martha E. Pollack, Colleen E. McCarthy, Sailesh Ramakrishnan, Ioannis Tsamardinos
    Pages 179-192
  13. Dilip Kumar Pratihar, Wolfgang Bibel
    Pages 193-210
  14. Paul Rybski, Sascha Stoeter, Maria Gini, Dean Hougen, Nikolaos Papanikolopoulos
    Pages 211-225
  15. Frank Schönherr, Joachim Hertzberg
    Pages 249-269
  16. Shlomo Zilberstein, Richard Washington, Daniel S. Bernstein, Abdel-Illah Mouaddib
    Pages 270-289
  17. Back Matter
    Pages 291-291

About these proceedings

Introduction

In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. In NASA’s Deep Space program, for example, an - tonomous spacecraft controller, called the Remote Agent [5], has autonomously performed a scienti?c experiment in space. At Carnegie Mellon University, Xavier [6], another autonomous mobile robot, navigated through an o?ce - vironment for more than a year, allowing people to issue navigation commands and monitor their execution via the Internet. In 1998, Minerva [7] acted for 13 days as a museum tourguide in the Smithsonian Museum, and led several thousand people through an exhibition. These autonomous robots have in common that they rely on plan-based c- trol in order to achieve better problem-solving competence. In the plan-based approach, robots generate control actions by maintaining and executing a plan that is e?ective and has a high expected utility with respect to the robots’ c- rent goals and beliefs. Plans are robot control programs that a robot can not only execute but also reason about and manipulate [4]. Thus, a plan-based c- troller is able to manage and adapt the robot’s intended course of action — the plan — while executing it and can thereby better achieve complex and changing tasks.

Keywords

agents algorithms artificial intelligence learning probabilistic reasoning problem solving robot robotics

Editors and affiliations

  • Michael Beetz
    • 1
  • Joachim Hertzberg
    • 2
  • Malik Ghallab
    • 3
  • Martha E. Pollack
    • 4
  1. 1.Institut für Informatik IXTechnische Universität MünchenMünchenGermany
  2. 2.Fraunhofer-Institut, Autonome Intelligente Systeme (AIS)Sankt AugustinGermany
  3. 3.LAAS-CNRSToulouse cedexFrance
  4. 4.College of Engineering Dept. of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborUSA

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-37724-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-00168-3
  • Online ISBN 978-3-540-37724-5
  • Series Print ISSN 0302-9743