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dc.contributor.authorHover, Franz S.
dc.date.accessioned2010-10-15T18:00:05Z
dc.date.available2010-10-15T18:00:05Z
dc.date.issued2009-12
dc.date.submitted2009-10
dc.identifier.isbn978-1-4244-3803-7
dc.identifier.otherINSPEC Accession Number: 11046499
dc.identifier.urihttp://hdl.handle.net/1721.1/59381
dc.description.abstractBy combining a low-order model of forecast errors, the extended Kalman filter, and classical continuous optimization, we develop an integrated methodology for planning mobile sensor paths to sample continuous fields. Agent trajectories are developed that specifically take into account the fact that data collected will be used for near real-time assimilation with large predictive models. This aspect of the problem has significant implications because the trajectories generated are very different from those which do not take the assimilation step into account, and their performance in controlling error is notably better.en_US
dc.description.sponsorshipSingapore-MIT Alliance for Research and Technologyen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/IROS.2009.5354367en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceIEEEen_US
dc.titlePath planning for data assimilation in mobile environmental monitoring systemsen_US
dc.typeArticleen_US
dc.identifier.citationHover, F.S. “Path planning for data assimilation in mobile environmental monitoring systems.” Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. 2009. 213-218. ©2009 Institute of Electrical and Electronics Engineers.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.approverHover, Franz S.
dc.contributor.mitauthorHover, Franz S.
dc.relation.journalIEEE/RSJ International Conference on Intelligent Robots and Systems, 2009, IROS 2009en_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsHover, Franz S.en
dc.identifier.orcidhttps://orcid.org/0000-0002-2621-7633
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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