Ant Colony Optimization based Simultaneous Task Allocation and Path Planning of Autonomous Vehicles

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dc.contributor.author Kulatunga, Asela en_US
dc.contributor.author Liu, Dikai en_US
dc.contributor.author Dissanayake, Gamini en_US
dc.contributor.author Siyambalapitiya, S en_US
dc.contributor.editor I-Ming Chen, K.C. Tan en_US
dc.date.accessioned 2009-11-09T05:36:07Z
dc.date.available 2009-11-09T05:36:07Z
dc.date.issued 2006 en_US
dc.identifier 2006005192 en_US
dc.identifier.citation Kulatunga Asela et al. 2006, 'Ant Colony Optimization based Simultaneous Task Allocation and Path Planning of Autonomous Vehicles', IEEE, Bangkok, Thailand, pp. 823-828. en_US
dc.identifier.issn 1-4244-0023-6 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2654
dc.description.abstract This paper applies a meta-heuristic based ant colony optimization (ACO) technique for simultaneous task allocation and path planning of automated guided vehicles (AGV) in material handling. ACO algorithm allocates tasks to AGVs based on collision free path obtained by a proposed path and motion planning algorithm. The validity of this approach is investigated by applying it to different task and AGV combinations which have different initial settings. For small combinations, i.e. small number of tasks and vehicles, the quality of the ACO solution is compared against the optimal results obtained from exhaustive search mechanism. This approach has shown near optimal results. For larger combinations, ACO solutions are compared with simulated annealing algorithm which is another commonly used meta-heuristic approach. The results show that ACO solutions have slightly better performance than that of simulated annealing algorithm en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/ICCIS.2006.252349 en_US
dc.title Ant Colony Optimization based Simultaneous Task Allocation and Path Planning of Autonomous Vehicles en_US
dc.parent Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Bangkok, Thailand en_US
dc.identifier.startpage 823 en_US
dc.identifier.endpage 828 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference.location Bangkok, Thailand en_US
dc.for 080100 en_US
dc.personcode 10076735 en_US
dc.personcode 000350 en_US
dc.personcode 011224 en_US
dc.personcode 0000029688 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE International Conference on Cybernetics and Intelligent Systems en_US
dc.date.activity 20060607 en_US
dc.location.activity Bangkok, Thailand en_US
dc.description.keywords Ant colony, optimization, task allocation, path planning, autonomous vehicles en_US


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