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dc.contributor.authorTemizer, Selim
dc.contributor.authorKochenderfer, Mykel J.
dc.contributor.authorKaelbling, Leslie P.
dc.contributor.authorLozano-Perez, Tomas
dc.contributor.authorKuchar, James K.
dc.date.accessioned2011-02-24T23:10:17Z
dc.date.available2011-02-24T23:10:17Z
dc.date.issued2010-08
dc.identifier.otherAIAA 2010-8040
dc.identifier.urihttp://hdl.handle.net/1721.1/61341
dc.descriptionURL to conference siteen_US
dc.description.abstractBefore unmanned aircraft can fly safely in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft con guration, we investigate the automatic generation of collision avoidance algorithms given models of aircraft dynamics, sensor performance, and intruder behavior. By formulating the problem of collision avoidance as a Markov Decision Process (MDP) for sensors that provide precise localization of the intruder aircraft, or a Partially Observable Markov Decision Process (POMDP) for sensors that have positional uncertainty or limited field-of-view constraints, generic MDP/POMDP solvers can be used to generate avoidance strategies that optimize a cost function that balances flight-plan deviation with collision. Experimental results demonstrate the suitability of such an approach using four diff erent sensor modalities and a parametric aircraft performance model.en_US
dc.description.sponsorshipUnited States. Air Force (Air Force contract #FA8721-05-C-0002)en_US
dc.language.isoen_US
dc.publisherAmerican Institute of Aeronautics and Astronauticsen_US
dc.relation.isversionofhttp://www.aiaa.org/content.cfm?pageid=230&lumeetingid=2358en_US
dc.rightsAttribution-Noncommercial-Share Alike 3.0 Unporteden_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleCollision Avoidance for Unmanned Aircraft using Markov Decision Processesen_US
dc.typeArticleen_US
dc.identifier.citationTemizer, Selim, et al. "Collision Avoidance for Unmanned Aircraft using Markov Decision Processes." AIAA Guidance, Navigation, and Control Conference, Toronto, Ontario, Aug. 2-5, 2010en_US
dc.contributor.departmentLincoln Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverKaelbling, Leslie P.
dc.contributor.mitauthorKaelbling, Leslie P.
dc.contributor.mitauthorKochenderfer, Mykel J.
dc.contributor.mitauthorTemizer, Selim
dc.contributor.mitauthorLozano-Perez, Tomas
dc.contributor.mitauthorKuchar, James K.
dc.relation.journalAIAA Guidance, Navigation, and Control Conference 2 - 5 August 2010, Toronto, Ontario Canadaen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dspace.orderedauthorsTemizer, Selim; Kochenderfer, Mykel J.; Kaelbling, Leslie P.; Lozano-Perez, Tomas; Kuchar, James K.
dc.identifier.orcidhttps://orcid.org/0000-0002-8657-2450
dc.identifier.orcidhttps://orcid.org/0000-0001-6054-7145
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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