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

Petar Ćurković; Bojan Jerbić; Tomislav Stipančić

doi:10.4028/www.scientific.net/SSP.147-149.74

Paper Titles

Design of In-Pipe Modular Robotic Systems
p.49

GPS Based Navigation of an Autonomous Mobile Vehicle
p.55

Mechatronics Engineering on the Example of a Multipurpose Mobile Robot
p.61

Selected Problems of Navigation of Educational Mobile Robot
p.67

Swarm-Based Approach to Path Planning Using Honey-Bees Mating Algorithm and ART Neural Network
p.74

The Behaviour Based Area Coverage of Unknown Environment by Autonomous Mobile Robot Using Modified "The Way of the Ox" Algorithm
p.80

Intelligent Live Environment Design with Assistive Robots for Vulnerable Persons
p.86

Localization of Mobile Robot Using Radio Waves
p.95

Agent-Component Design of Smart Appliances
p.101

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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.