Self-organizing map for the multi-goal path planning with polygonal goals

Authors:
Jan Faigl;Libor Přeučil
Affiliations:
Czech Technical University in Prague, Department of Cybernetics;Czech Technical University in Prague, Department of Cybernetics
Venue:
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Year:
2011

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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 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 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.