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dc.contributor.authorFraser, Douglas
dc.contributor.authorGiaquinta, Ruben
dc.contributor.authorHoffmann, Ruth
dc.contributor.authorIreland, Murray
dc.contributor.authorMiller, Alice
dc.contributor.authorNorman, Gethin
dc.date.accessioned2020-05-07T11:30:01Z
dc.date.available2020-05-07T11:30:01Z
dc.date.issued2020-07
dc.identifier266448813
dc.identifierccf0b5be-71a3-4308-a07e-d245faa536ab
dc.identifier85083778492
dc.identifier000555986700002
dc.identifier.citationFraser , D , Giaquinta , R , Hoffmann , R , Ireland , M , Miller , A & Norman , G 2020 , ' Collaborative models for autonomous systems controller synthesis ' , Formal Aspects of Computing , vol. 32 , no. 2-3 , pp. 157–186 . https://doi.org/10.1007/s00165-020-00508-1en
dc.identifier.issn0934-5043
dc.identifier.otherORCID: /0000-0002-1011-5894/work/73701368
dc.identifier.urihttps://hdl.handle.net/10023/19897
dc.descriptionFunding: UK EPSRC grants EP/N508792/1, EP/N007565 and EC/P51133X/1.en
dc.description.abstractWe show how detailed simulation models and abstract Markov models can be developed collaboratively to generate and implement effective controllers for autonomous agent search and retrieve missions. We introduce a concrete simulation model of an Unmanned Aerial Vehicle (UAV). We then show how the probabilistic model checker PRISM is used for optimal strategy synthesis for a sequence of scenarios relevant to UAVs and potentially other autonomous agent systems. For each scenario we demonstrate how it can be modelled using PRISM, give model checking statistics and present the synthesised optimal strategies. We then show how our strategies can be returned to the controller for the simulation model and provide experimental results to demonstrate the effectiveness of one such strategy. Finally we explain how our models can be adapted, using symmetry, for use on larger search areas, and demonstrate the feasibility of this approach.
dc.format.extent30
dc.format.extent2849254
dc.language.isoeng
dc.relation.ispartofFormal Aspects of Computingen
dc.subjectAutonomous systemsen
dc.subjectFormal verificationen
dc.subjectProbabilistic model checkingen
dc.subjectStrategy synthesisen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectT-NDASen
dc.subject.lccQA75en
dc.titleCollaborative models for autonomous systems controller synthesisen
dc.typeJournal articleen
dc.contributor.sponsorEPSRCen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews. St Andrews GAP Centreen
dc.identifier.doi10.1007/s00165-020-00508-1
dc.description.statusPeer revieweden
dc.date.embargoedUntil2020-04-16
dc.identifier.grantnumberEP/N007565/1en


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