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

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dc.contributor.author Kulatunga, AK
dc.contributor.author Skinner, B
dc.contributor.author Liu, D
dc.contributor.author Nguyen, HT
dc.contributor.editor Tarn, TJ
dc.contributor.editor Chen, SB
dc.contributor.editor Zhou, C
dc.date.accessioned 2010-07-15T07:25:45Z
dc.date.issued 2007-01
dc.identifier.citation Robotic Welding, Intelligence and Automation, 2007, 1, pp. 409 - 420
dc.identifier.isbn 978-3-540-73373-7
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.
dc.publisher Springer
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon 10.1007/978-3-540-73374-4_49
dc.title Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster
dc.type Chapter
dc.parent Robotic Welding, Intelligence and Automation
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 0906 Electrical and Electronic Engineering
dc.for 0103 Numerical and Computational Mathematics
dc.for 0102 Applied Mathematics
dc.personcode 840115
dc.personcode 000350
dc.personcode 995215
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
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
pubs.organisational-group /University of Technology Sydney/Strength - Health Technologies
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
pubs.consider-herdc true
utslib.collection.history General (ID: 2)


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