Tracking and sensor coverage of spatio-temporal quantities using a swarm of artificial foraging agents

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dc.contributor.authorOyekan, John
dc.contributor.authorGu, D.
dc.contributor.authorHu, H.
dc.date.accessioned2016-12-06T11:10:16Z
dc.date.available2016-12-06T11:10:16Z
dc.date.issued2016-11-09
dc.description.abstractUsing a network of mobile sensors to track and map a dynamic spatio-temporal process in the environment is one of the current challenges in multi-agent systems. In this work, a distributed probabilistic multi-agent algorithm inspired by the bacterium foraging behavior is presented. The novelty of the algorithm lies in being capable of tracking and mapping a spatio-temporal quantity without the need of machine learning, estimation algorithms or future planning. This is unlike most current techniques that rely heavily on machine learning to estimate the distribution as well as the profile of spatio-temporal quantities. The experimental studies carried out in this work show that the algorithm works well by following the concentration gradient of a dynamic plume created under diffusive conditions. Furthermore, the algorithm is inherently capable of finding the source of a diffusive spatio-temporal quantity as well as performing environmental exploration. It is computationally tractable for simple agents, shown to adapt to its environment and can deal successfully with noise in sensor readings as well as in robot dynamics.en_UK
dc.identifier.citationJohn Oyekan, Dongbing Gu and Huosheng Hu. Tracking and sensor coverage of spatio-temporal quantities using a swarm of artificial foraging agents. Journal of Bionic Engineering, Volume 13, Issue 4, October 2016, Pages 679–689.en_UK
dc.identifier.issn1672-6529
dc.identifier.urihttp://dx.doi.org/10.1016/S1672-6529(16)60339-6
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/11088
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectbioinspired algorithmen_UK
dc.subjectartificial foraging swarmen_UK
dc.subjectspatio-temporal mappingen_UK
dc.titleTracking and sensor coverage of spatio-temporal quantities using a swarm of artificial foraging agentsen_UK
dc.typeArticleen_UK

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