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dc.contributor.authorCheung, B.en
dc.contributor.authorDavey, S.en
dc.contributor.authorGray, D.en
dc.identifier.citationProceedings of the 13th International conference on Information fusion (FUSION), 26-29 July, 2010; pp.1-8en
dc.description.abstractThis paper considers the problem of automati- cally coordinating multiple platforms to explore an unknown environment. The goal is a planning algorithm that provides a path for each platform in such a way that the collection of platforms cooperatively sense the environment in a glob- ally efficient manner. A collection of discrete locales of interest is assumed to be known and the platforms use these as waypoints. The key feature of the method is to treat the assignment of locales to platforms as a target tracking problem. This paper compares the use of the Probabilistic Multi Hypothesis Tracker (PMHT) as a method of performing multiple platform batch data association with the Genetic Algo-rithm to solve the modified Multi Travelling Salesman Problem.en
dc.description.statementofresponsibilityBrian Cheung, Samuel Davey and Douglas Grayen
dc.rights© Copyright 2011 IEEE – All Rights Reserveden
dc.titleComparison of the pmht path planning algorithm with the genetic algorithm for multiple platformsen
dc.typeConference paperen
dc.contributor.conferenceInternational conference on information fusion (13th : 2010 : Edinburgh, UK)en
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Electrical and Electronic Engineering publications

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