Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/84723
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dc.contributor.authorSathyaraj, B.M.-
dc.contributor.authorJain, L.-
dc.contributor.authorFinn, A.-
dc.contributor.authorDrake, S.-
dc.date.issued2008-
dc.identifier.citationFuzzy Optimization and Decision Making, 2008; 7(3):257-267-
dc.identifier.issn1568-4539-
dc.identifier.issn1573-2908-
dc.identifier.urihttp://hdl.handle.net/2440/84723-
dc.description.abstractUnmanned aerial vehicles (UAVs) are used in team for detecting targets and keeping them in its sensor range. There are various algorithms available for searching and monitoring targets. The complexity of the search algorithm increases if the number of nodes is increased. This paper focuses on multi UAVs path planning and Path Finding algorithms. Number of Path Finding and Search algorithms was applied to various environments, and their performance compared. The number of searches and also the computation time increases as the number of nodes increases. The various algorithms studied are Dijkstra’s algorithm, Bellman Ford’s algorithm, Floyd-Warshall’s algorithm and the AStar algorithm. These search algorithms were compared. The results show that the AStar algorithm performed better than the other search algorithms. These path finding algorithms were compared so that a path for communication can be established and monitored.-
dc.description.statementofresponsibilityB. Moses Sathyaraj, L. C. Jain, A. Finn, S. Drake-
dc.language.isoen-
dc.publisherSpringer US-
dc.rights© Springer Science+Business Media, LLC 2008-
dc.subjectPathfinding-
dc.subjectAStar-
dc.subjectDijkstra-
dc.subjectDistance vector algorithms-
dc.titleMultiple UAVs path planning algorithms: a comparative study-
dc.typeJournal article-
dc.identifier.doi10.1007/s10700-008-9035-0-
pubs.publication-statusPublished-
dc.identifier.orcidDrake, S. [0000-0003-3066-7837]-
Appears in Collections:Aurora harvest 2
Physics publications

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