Oyekan, John and Gu, Dongbing and Hu, Huosheng (2013) Visual Imaging of Invisible Hazardous Substances Using Bacterial Inspiration. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43 (5). pp. 1105-1115. DOI https://doi.org/10.1109/tsmca.2012.2231410
Oyekan, John and Gu, Dongbing and Hu, Huosheng (2013) Visual Imaging of Invisible Hazardous Substances Using Bacterial Inspiration. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43 (5). pp. 1105-1115. DOI https://doi.org/10.1109/tsmca.2012.2231410
Oyekan, John and Gu, Dongbing and Hu, Huosheng (2013) Visual Imaging of Invisible Hazardous Substances Using Bacterial Inspiration. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43 (5). pp. 1105-1115. DOI https://doi.org/10.1109/tsmca.2012.2231410
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. © 2013 IEEE.
Item Type: | Article |
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Uncontrolled Keywords: | Bacterium-inspired algorithm; environmental monitoring; optimal coverage; simplistic agents; visual imaging |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 09 Sep 2014 12:24 |
Last Modified: | 06 Dec 2024 16:48 |
URI: | http://repository.essex.ac.uk/id/eprint/9260 |