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dc.contributor.authorTurner, Joanna
dc.contributor.authorMeng, Qinggang
dc.contributor.authorSchaefer, Gerald
dc.contributor.authorWhitbrook, Amanda
dc.contributor.authorSoltoggio, Andrea
dc.date.accessioned2017-10-24T09:46:27Z
dc.date.available2017-10-24T09:46:27Z
dc.date.issued2017-09-28
dc.identifier.citationTurner, J. et al (2017) 'Distributed Task Rescheduling With Time Constraints for the Optimization of Total Task Allocations in a Multirobot System', IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2017.2743164en
dc.identifier.issn21682267
dc.identifier.doi10.1109/TCYB.2017.2743164
dc.identifier.urihttp://hdl.handle.net/10545/621889
dc.description.abstractThis paper considers the problem of maximizing the number of task allocations in a distributed multirobot system under strict time constraints, where other optimization objectives need also be considered. It builds upon existing distributed task allocation algorithms, extending them with a novel method for maximizing the number of task assignments. The fundamental idea is that a task assignment to a robot has a high cost if its reassignment to another robot creates a feasible time slot for unallocated tasks. Multiple reassignments among networked robots may be required to create a feasible time slot and an upper limit to this number of reassignments can be adjusted according to performance requirements. A simulated rescue scenario with task deadlines and fuel limits is used to demonstrate the performance of the proposed method compared with existing methods, the consensus-based bundle algorithm and the performance impact (PI) algorithm. Starting from existing (PI-generated) solutions, results show up to a 20% increase in task allocations using the proposed method.
dc.description.sponsorshipEPSRC Grant EP/J011525/1en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/8053456/en
dc.rightsArchived with thanks to IEEE Transactions on Cyberneticsen
dc.subjectDistributed task-allocationen
dc.subjectMultiagent systemsen
dc.subjectVehicle routingen
dc.subjectResource managementen
dc.subjectRobotsen
dc.subjectOptimizationen
dc.subjectTime factorsen
dc.subjectFuel cellsen
dc.titleDistributed task rescheduling with time constraints for the optimization of total task allocations in a multirobot systemen
dc.typeArticleen
dc.identifier.eissn21682275
dc.contributor.departmentLoughborough Universityen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalIEEE Transactions on Cyberneticsen
refterms.dateFOA2019-02-28T16:08:54Z
html.description.abstractThis paper considers the problem of maximizing the number of task allocations in a distributed multirobot system under strict time constraints, where other optimization objectives need also be considered. It builds upon existing distributed task allocation algorithms, extending them with a novel method for maximizing the number of task assignments. The fundamental idea is that a task assignment to a robot has a high cost if its reassignment to another robot creates a feasible time slot for unallocated tasks. Multiple reassignments among networked robots may be required to create a feasible time slot and an upper limit to this number of reassignments can be adjusted according to performance requirements. A simulated rescue scenario with task deadlines and fuel limits is used to demonstrate the performance of the proposed method compared with existing methods, the consensus-based bundle algorithm and the performance impact (PI) algorithm. Starting from existing (PI-generated) solutions, results show up to a 20% increase in task allocations using the proposed method.


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