2.50
Hdl Handle:
http://hdl.handle.net/10547/279221
Title:
Visual imaging of invisible hazardous substances using bacterial inspiration
Authors:
Oyekan, John; Gu, Dongbing; Hu, Huosheng
Abstract:
Providing a visual image of a hazardous substance such as nerve gas or nuclear radiation using multiple robotic agents could be very useful particularly when the substance is invisible. Such visual representation could show where the hazardous substance concentration is highest through the deployment of a higher density of robotic agents to that area enabling humans to avoid such areas. We present an algorithm that is capable of doing the aforementioned with very minimal cost when compared with other techniques such as Voronoi partition methods. Using a mathematical proof, we show that the algorithm would always converge to the distribution of a spatial quantity under investigation. The mathematical model of the bacterium as developed by Berg and Brown is used in this paper, and through simulations and physical experiments, we show that a controller based upon the model is capable of being used to visually represent an invisible spatial hazardous substance using simplistic agents with the future possibility of the same algorithm being used to track a rapidly changing spatiotemporal substance. We believe that the algorithm has this potential because of its low communication and computational needs.
Citation:
Oyekan, J.; Gu, D. and Hu, H. (2013) 'Visual Imaging of Invisible Hazardous Substances Using Bacterial Inspiration,' Systems, Man, and Cybernetics: Systems, IEEE Transactions on , 99: pp. 1-11
Journal:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Issue Date:
2013
URI:
http://hdl.handle.net/10547/279221
DOI:
10.1109/TSMCA.2012.2231410
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6425508
Type:
Article
Language:
en
ISSN:
2168-2216; 2168-2232
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorOyekan, Johnen_GB
dc.contributor.authorGu, Dongbingen_GB
dc.contributor.authorHu, Huoshengen_GB
dc.date.accessioned2013-04-07T21:38:49Z-
dc.date.available2013-04-07T21:38:49Z-
dc.date.issued2013-
dc.identifier.citationOyekan, J.; Gu, D. and Hu, H. (2013) 'Visual Imaging of Invisible Hazardous Substances Using Bacterial Inspiration,' Systems, Man, and Cybernetics: Systems, IEEE Transactions on , 99: pp. 1-11en_GB
dc.identifier.issn2168-2216-
dc.identifier.issn2168-2232-
dc.identifier.doi10.1109/TSMCA.2012.2231410-
dc.identifier.urihttp://hdl.handle.net/10547/279221-
dc.description.abstractProviding a visual image of a hazardous substance such as nerve gas or nuclear radiation using multiple robotic agents could be very useful particularly when the substance is invisible. Such visual representation could show where the hazardous substance concentration is highest through the deployment of a higher density of robotic agents to that area enabling humans to avoid such areas. We present an algorithm that is capable of doing the aforementioned with very minimal cost when compared with other techniques such as Voronoi partition methods. Using a mathematical proof, we show that the algorithm would always converge to the distribution of a spatial quantity under investigation. The mathematical model of the bacterium as developed by Berg and Brown is used in this paper, and through simulations and physical experiments, we show that a controller based upon the model is capable of being used to visually represent an invisible spatial hazardous substance using simplistic agents with the future possibility of the same algorithm being used to track a rapidly changing spatiotemporal substance. We believe that the algorithm has this potential because of its low communication and computational needs.en_GB
dc.language.isoenen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6425508en_GB
dc.rightsArchived with thanks to IEEE Transactions on Systems, Man, and Cybernetics: Systemsen_GB
dc.subjectbacterium-inspired algorithmen_GB
dc.subjectenvironmental monitoringen_GB
dc.titleVisual imaging of invisible hazardous substances using bacterial inspirationen
dc.typeArticleen
dc.identifier.journalIEEE Transactions on Systems, Man, and Cybernetics: Systemsen_GB
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