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

Abstract:

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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 et al., "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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Price:

$35.00

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