Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster

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dc.contributor.author Kulatunga, Asela en_US
dc.contributor.author Liu, Dikai en_US
dc.contributor.author Nguyen, Hung en_US
dc.contributor.author Skinner, Brad en_US
dc.contributor.editor Tzyh-Jong Tarn, Shan-Ben Chen, Changjiu Zhou en_US
dc.date.accessioned 2010-07-15T07:25:45Z
dc.date.available 2010-07-15T07:25:45Z
dc.date.issued 2007 en_US
dc.identifier 2006009429 en_US
dc.identifier.citation Kulatunga Asela et al. 2007, 'Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster', in http://dx.doi.org/10.1007/978-3-540-73374-4_49 (ed.), Springer-Verlag, Heidelberg, pp. 409-420. en_US
dc.identifier.issn 978-3-540-73373-7 en_US
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/12741
dc.description.abstract Task allocation and motion coordination are the main factors that should be consi-dered in the coordination of multiple autonomous vehicles in material handling systems. Presently, these factors are handled in different stages, leading to a reduction in optimality and efficiency of the overall coordination. However, if these issues are solved simultaneously we can gain near optimal results. But, the simultaneous approach contains additional algorithmic complexities which increase computation time in the simulation environment. This work aims to reduce the computation time by adopting a parallel and distributed computation strategy for Simultaneous Task Allocation and Motion Coordination (STAMC). In the simulation experiments, each cluster node executes the motion coordination algorithm for each autonomous vehicle. This arrangement enables parallel computation of the expensive STAMC algorithm. Parallel and distributed computation is performed directly within the interpretive MATLAB environment. Results show the parallel and distributed approach provides sub-linear speedup compared to a single centralised computing node. en_US
dc.language en_US
dc.publisher Springer en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/978-3-540-73374-4_49 en_US
dc.rights The original publication is available at www.springerlink.com en_US
dc.title Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster en_US
dc.parent Robotic Welding, Intelligence and Automation en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Heidelberg en_US
dc.identifier.startpage 409 en_US
dc.identifier.endpage 420 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 010200 en_US
dc.personcode 10076735 en_US
dc.personcode 995215 en_US
dc.personcode 000350 en_US
dc.personcode 840115 en_US
dc.percentage 34 en_US
dc.classification.name Applied Mathematics en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords en_US
dc.staffid en_US
dc.staffid 840115 en_US


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