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International Conference on Artificial Neural Networks

ICANN 1997: Artificial Neural Networks — ICANN'97 pp 793–798Cite as

A hybrid path planning system combining the A*-method and RBF-networks

  • Part V: Robotics, Adaptive Autonomous Agents, and Control
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

Abstract

In this paper we propose a novel, hybrid path planning system based on an extended A*-method in combination with special RBF-networks. The output of the A*-method, a set of classified cells, is used to train two variants of RBF-networks. Global RBF-networks (GRBF-networks) represent a wide area around the optimal path and generate smooth paths. Local RBF-networks (LRBF-networks) represent a small area around the optimal path and guarantee an obstacle-free “tube” surrounding this path. GRBF- and LRBF-networks are tested in different 3D- and 6D-scenarios.

Parts of this work have been supported by the Federal Ministry for Education, Science, Research and Technology (BMBF).

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bonn, Germany

    Thomas Frontzek, Nils Goerke & Rolf Eckmiller

Authors
  1. Thomas Frontzek
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  2. Nils Goerke
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  3. Rolf Eckmiller
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Frontzek, T., Goerke, N., Eckmiller, R. (1997). A hybrid path planning system combining the A*-method and RBF-networks. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020251

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  • DOI: https://doi.org/10.1007/BFb0020251

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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