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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System

Swarm intelligence can be described as a complex behaviour generated from a large number of individual agents, where each agent follows very simple rules. It is actually inspired by understanding the decentralized mechanisms in the organization of natural swarms such as the birds, the ants, the bees...

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Main Author: Abidin, Zulkifli Zainal
Format: Thesis
Language:English
Published: 2013
Subjects:
TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Online Access:http://eprints.usm.my/45234/1/Zulkifli%20Bin%20Zainal%20Abidin24.pdf
http://eprints.usm.my/45234/
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spelling my.usm.eprints.45234 http://eprints.usm.my/45234/ Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System Abidin, Zulkifli Zainal TK1-9971 Electrical engineering. Electronics. Nuclear engineering Swarm intelligence can be described as a complex behaviour generated from a large number of individual agents, where each agent follows very simple rules. It is actually inspired by understanding the decentralized mechanisms in the organization of natural swarms such as the birds, the ants, the bees, the glowworms, and the fireflies. Observation of these biological behaviour has given birth to swarm robotics whereby robots have the capability to work with one another in a group to achieve the same kind of parallelism, robustness and collective capabilities. A collective behaviour movement strategy such as a “source search” and “aggregation” are commonly exhibited by the animals while finding their source of food. However, the situation for the robots is to find the source of odour, light, and sound. Meanwhile, there has been mounting interest, particularly for finding the deepest location in lakes and dams for bathymetric survey systems. Using the existing lawnmower methods incur substantial costs in terms of time, accuracy and reliability. Therefore, the usage of a swarming robotic system is proposed. In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. The fruit flies or Drosophila Melanogaster movement strategy offers some advantages such as strategic 'search-aggregation' cycle, distribution of moving patterns with Levy Random, information sharing in real-time, and reduction of controller parameters during movements. A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm). 2013-07 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/45234/1/Zulkifli%20Bin%20Zainal%20Abidin24.pdf Abidin, Zulkifli Zainal (2013) Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic TK1-9971 Electrical engineering. Electronics. Nuclear engineering
spellingShingle TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Abidin, Zulkifli Zainal
Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
description Swarm intelligence can be described as a complex behaviour generated from a large number of individual agents, where each agent follows very simple rules. It is actually inspired by understanding the decentralized mechanisms in the organization of natural swarms such as the birds, the ants, the bees, the glowworms, and the fireflies. Observation of these biological behaviour has given birth to swarm robotics whereby robots have the capability to work with one another in a group to achieve the same kind of parallelism, robustness and collective capabilities. A collective behaviour movement strategy such as a “source search” and “aggregation” are commonly exhibited by the animals while finding their source of food. However, the situation for the robots is to find the source of odour, light, and sound. Meanwhile, there has been mounting interest, particularly for finding the deepest location in lakes and dams for bathymetric survey systems. Using the existing lawnmower methods incur substantial costs in terms of time, accuracy and reliability. Therefore, the usage of a swarming robotic system is proposed. In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. The fruit flies or Drosophila Melanogaster movement strategy offers some advantages such as strategic 'search-aggregation' cycle, distribution of moving patterns with Levy Random, information sharing in real-time, and reduction of controller parameters during movements. A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm).
format Thesis
author Abidin, Zulkifli Zainal
author_facet Abidin, Zulkifli Zainal
author_sort Abidin, Zulkifli Zainal
title Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
title_short Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
title_full Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
title_fullStr Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
title_full_unstemmed Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
title_sort fruit-fly based searching algorithm for cooperative swarming robotic system
publishDate 2013
url http://eprints.usm.my/45234/1/Zulkifli%20Bin%20Zainal%20Abidin24.pdf
http://eprints.usm.my/45234/
_version_ 1643711227745009664
score 13.211869

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