Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis

Animals such as silkworm moths, dogs and blue crabs have exhibited odour localization capabilities in nature. This amazing ability is exhibited in complex airflow conditions which produces highly dynamic and unpredictable gas dispersion. Harnessing this capability will enable robots to be deployed i...

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Bibliographic Details
Format:	Thesis
Language:	English
Subjects:	Swarm intelligence Robotics Odour Gas sensing Gas source localization
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/4/Syed%20Muhammad.pdf
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id	my-unimap-72938
record_format	uketd_dc
spelling	my-unimap-729382021-12-17T03:41:02Z Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis Ali Yeon, Md. Shakaff, Prof. Dr. Animals such as silkworm moths, dogs and blue crabs have exhibited odour localization capabilities in nature. This amazing ability is exhibited in complex airflow conditions which produces highly dynamic and unpredictable gas dispersion. Harnessing this capability will enable robots to be deployed in critical and high-value applications such as search and rescue, entry point security applications, and environmental monitoring in industrial and urban settings. This thesis documents the research in swarm intelligence for gas source localization. Using swarm intelligence to achieve this task is envisaged to be more practical and economical compared to single robot implementations. Currently, few works have been presented on multi-robot systems in gas source localization; much less using swarm intelligence. This research aims to fill in the research gaps in gas source localization using swarm intelligence. However, current mobile olfaction experimental methods tend to oversimplify the actual problems thus reducing the findings’ impact in advancing this research field. Furthermore, lack of experimental realism reduces the reproducibility of the previously presented works in real world conditions. To overcome this limitation, this research uses recorded real-time gas dispersion in robot simulations. A real-time gas dispersion monitoring system consisting 72-gas sensors was built to record the gas dispersion in the experiment area. The recorded real-time data stream was then used in simulations to accurately recreate realworld experimental conditions in a simulation environment. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72938 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/1/Page%201-24.pdf 337c9f77694df16aff2a69508df9e731 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/2/Full%20text.pdf 29763df986c937c59e9985c4bf029ce7 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/4/Syed%20Muhammad.pdf 189d54e3e445b3970b993bb3a517c8eb Universiti Malaysia Perlis (UniMAP) Swarm intelligence Robotics Odour Gas sensing Gas source localization School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Ali Yeon, Md. Shakaff, Prof. Dr.
topic	Swarm intelligence Robotics Odour Gas sensing Gas source localization
spellingShingle	Swarm intelligence Robotics Odour Gas sensing Gas source localization Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
description	Animals such as silkworm moths, dogs and blue crabs have exhibited odour localization capabilities in nature. This amazing ability is exhibited in complex airflow conditions which produces highly dynamic and unpredictable gas dispersion. Harnessing this capability will enable robots to be deployed in critical and high-value applications such as search and rescue, entry point security applications, and environmental monitoring in industrial and urban settings. This thesis documents the research in swarm intelligence for gas source localization. Using swarm intelligence to achieve this task is envisaged to be more practical and economical compared to single robot implementations. Currently, few works have been presented on multi-robot systems in gas source localization; much less using swarm intelligence. This research aims to fill in the research gaps in gas source localization using swarm intelligence. However, current mobile olfaction experimental methods tend to oversimplify the actual problems thus reducing the findings’ impact in advancing this research field. Furthermore, lack of experimental realism reduces the reproducibility of the previously presented works in real world conditions. To overcome this limitation, this research uses recorded real-time gas dispersion in robot simulations. A real-time gas dispersion monitoring system consisting 72-gas sensors was built to record the gas dispersion in the experiment area. The recorded real-time data stream was then used in simulations to accurately recreate realworld experimental conditions in a simulation environment.
format	Thesis
title	Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
title_short	Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
title_full	Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
title_fullStr	Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
title_full_unstemmed	Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
title_sort	odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72938/4/Syed%20Muhammad.pdf
_version_	1747836879656452096

Odour source localization strategy for multiple robots using swarm intelligence with odour-gated anemotaxis

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