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Learning to Execute Navigation Plans

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KI 2001: Advances in Artificial Intelligence (KI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2174))

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Abstract

Most state-of-the-art navigation systems for autonomous service robots decompose navigation into global navigation planning and local reactive navigation. While the methods for navigation planning and local navigation are well understood, the plan execution problem, the problem of how to generate and parameterize local navigation tasks from a given navigation plan, is largely unsolved. This article describes how a robot can autonomously learn to execute navigation plans. We formalize the problem as a Markov Decision Problem (mdp), discuss how it can be simplified to make its solution feasible, and describe how the robot can acquire the necessary action models. We show, both in simulation and on a RWI B21 mobile robot, that the learned models are able to produce competent navigation behavior.

The research reported in this paper is partly funded by the Deutsche Forschungsgemeinschaft (DFG) under contract number BE 2200/3-1.

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Authors
  1. Thorsten Belker
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  2. Michael Beetz
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Editor information

Editors and Affiliations

  1. RWTH Aachen, Theoretical Computer Science, Ahornstrasse 55, 52074, Aachen, Germany

    Franz Baader

  2. Intelligent Systems Department, University of Leipzig, Computer Science Institute, Augustusplatz 10-11, 04109, Leipzig, Germany

    Gerhard Brewka

  3. Institute of Information Systems Knowledge-Based Systems Group, Vienna University of Technology, Favoritenstrasse 11, 1040, Wien, Austria

    Thomas Eiter

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© 2001 Springer-Verlag Berlin Heidelberg

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Belker, T., Beetz, M. (2001). Learning to Execute Navigation Plans. In: Baader, F., Brewka, G., Eiter, T. (eds) KI 2001: Advances in Artificial Intelligence. KI 2001. Lecture Notes in Computer Science(), vol 2174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45422-5_30

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  • DOI: https://doi.org/10.1007/3-540-45422-5_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42612-7

  • Online ISBN: 978-3-540-45422-9

  • eBook Packages: Springer Book Archive

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