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dc.contributor.authorSzwaykowska, Klementyna
dc.contributor.authorZhang, Fumin
dc.date.accessioned2011-05-16T17:03:16Z
dc.date.available2011-05-16T17:03:16Z
dc.date.issued2010-12
dc.identifier.citationK. Szwaykowska and Fumin Zhang, “A Lower Bound for Controlled Lagrangian Particle Tracking Error, ” in Proc.49th IEEE Conference on Decision and Control (CDC 2010), 4353-4358, 2010.en_US
dc.identifier.issn0743-1546
dc.identifier.urihttp://hdl.handle.net/1853/38884
dc.descriptionDigital Object Identifier: 10.1109/CDC.2010.5718170en_US
dc.descriptionU.S. Government work not protected by U.S. copyright
dc.description.abstractAutonomous underwater vehicles are flexible mobile platforms for ocean sampling and surveillance missions. However, navigation of these vehicles in unstructured, highly variable ocean environments poses a significant challenge. Model-based prediction of vehicle position may be used to improve navigation capability, but prediction error exists due to limited resolution and accuracy of flow values obtained from ocean models that calculate flow velocity at discrete grid points. We present a theoretical lower bound on the steady-state error in position prediction for underwater vehicles using ocean model flow data and show that it is determined by the gridsize used by the ocean models. Our conclusions are justified by simulation and data collected during an ocean experiment.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectAutonomous underwater vehiclesen_US
dc.subjectPosition predictionen_US
dc.subjectNavigationen_US
dc.titleA Lower Bound for Controlled Lagrangian Particle Tracking Erroren_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineering
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machines


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