Paper Title:
Swarm-Based Approach to Path Planning Using Honey-Bees Mating Algorithm and ART Neural Network
  Abstract

In this paper, an integration of Honey bees mating algorithm (HBMA) and adaptive resonance theory neural network (ART1) for efficient path planning of a mobile robot in a static environment is presented. The robot must find shortest route from given origin to the target position. Moreover, it should be able to memorize the environment and, if it faces known world, execute already learned trajectory found by HBMA solver, or solve the world and memorize the trajectory for the given environment. This is done using Adaptive Resonance Theory based neural network. This way simulated robot is able to navigate through environment and to continuously increase its knowledge.

  Info
Periodical
Solid State Phenomena (Volumes 147-149)
Edited by
Zdzislaw Gosiewski and Zbigniew Kulesza
Pages
74-79
DOI
10.4028/www.scientific.net/SSP.147-149.74
Citation
P. Ćurković, B. Jerbić, T. Stipančić, "Swarm-Based Approach to Path Planning Using Honey-Bees Mating Algorithm and ART Neural Network", Solid State Phenomena, Vols. 147-149, pp. 74-79, 2009
Online since
January 2009
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$32.00
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