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Probabilistic, Prediction-Based Schedule Debugging for Autonomous Robot Office Couriers

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KI-99: Advances in Artificial Intelligence (KI 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1701))

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Abstract

Acting efficiently and meeting deadlines requires autonomous robots to schedule their activities. It also requires them to act flexibly: to exploit opportunities and avoid problems as they occur. Scheduling activities to meet these requirements is an important research problem in its own right. In addition, it provides us with a problem domain where modern symbolic AI planning techniques could considerably improve the robots’ behavior.

This paper describes ppsd, a novel planning technique that enables autonomous robots to impose order constraints on concurrent percept-driven plans to increase the plans’ efficiency. The basic idea is to generate a schedule under simplified conditions and then to iteratively detect, diagnose, and eliminate behavior flaws caused by the schedule based on a small number of randomly sampled symbolic execution scenarios. The paper discusses the integration of ppsd into the controller of an autonomous robot office courier and gives an example of its use.

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References

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Author information

Authors and Affiliations

  1. Dept. of Computer Science III, University of Bonn, D-53117, Bonn, Germany

    Michael Beetz & Maren Bennewitz

  2. Department of Computer Science V, Aachen Univ. of Technology, D-52056, Aachen, Germany

    Henrik Grosskreutz

Authors
  1. Michael Beetz
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  2. Maren Bennewitz
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  3. Henrik Grosskreutz
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Editor information

Editors and Affiliations

  1. Institut für Informatik III, Universität Bonn, Römerstraße 164, D-53117, Bonn, Germany

    Wolfram Burgard  & Armin B. Cremers  & 

  2. GMD-Forschungszentrum Informationstechnik GmbH, SchloĂź Birlinghoven, D-53754, Sankt Augustin, Germany

    Thomas Cristaller

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© 1999 Springer-Verlag Berlin Heidelberg

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Beetz, M., Bennewitz, M., Grosskreutz, H. (1999). Probabilistic, Prediction-Based Schedule Debugging for Autonomous Robot Office Couriers. In: Burgard, W., Cremers, A.B., Cristaller, T. (eds) KI-99: Advances in Artificial Intelligence. KI 1999. Lecture Notes in Computer Science(), vol 1701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48238-5_20

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  • DOI: https://doi.org/10.1007/3-540-48238-5_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66495-6

  • Online ISBN: 978-3-540-48238-3

  • eBook Packages: Springer Book Archive

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