Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals

  • Jan Faigl
  • Libor Přeučil
Conference paper

DOI: 10.1007/978-3-642-21735-7_11

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6791)
Cite this paper as:
Faigl J., Přeučil L. (2011) Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals. In: Honkela T., Duch W., Girolami M., Kaski S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6791. Springer, Berlin, Heidelberg

Abstract

This paper presents a self-organizing map approach for the multi-goal path planning problem with polygonal goals. The problem is to find a shortest closed collision free path for a mobile robot operating in a planar environment represented by a polygonal map \({\cal W}\). The requested path has to visit a given set of areas where the robot takes measurements in order to find an object of interest. Neurons’ weights are considered as points in \({\cal W}\) and the solution is found as approximate shortest paths connecting the points (weights). The proposed self-organizing map has less number of parameters than a previous approach based on the self-organizing map for the traveling salesman problem. Moreover, the proposed algorithm provides better solutions within less computational time for problems with high number of polygonal goals.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jan Faigl
    • 1
  • Libor Přeučil
    • 1
  1. 1.Department of CyberneticsCzech Technical University in PragueCzech Republic

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