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dc.contributor.authorLiu, Linda Y.
dc.contributor.authorGoodin, Chris
dc.contributor.authorKala, Raju
dc.contributor.authorCarrrillo, Alex
dc.date.accessioned2010-10-14T20:13:16Z
dc.date.available2010-10-14T20:13:16Z
dc.date.issued2010-01
dc.date.submitted2009-10
dc.identifier.isbn978-1-4244-4548-6
dc.identifier.issn1930-0395
dc.identifier.otherINSPEC Accession Number: 11134514
dc.identifier.urihttp://hdl.handle.net/1721.1/59345
dc.description.abstractThe Virtual Autonomous Navigation Environment (VANE) is a high fidelity, physics-based simulation process that produces realistic simulated sensor output for use in the development and testing of Autonomous Mobility Systems (AMS). The VANE produces simulated sensor output for ranging and camera sensors that are characterized by a few easily determined input parameters. This flexibility allows for the efficient characterization of a sensor interaction with a particular AMS. This paper presents the development of these models and some initial results.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICSENS.2009.5398491en_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.titleSensor modeling for the virtual autonomous navigation environmenten_US
dc.typeArticleen_US
dc.identifier.citationGoodin, C. et al. “Sensor modeling for the Virtual Autonomous Navigation Environment.” Sensors, 2009 IEEE. 2009. 1588-1592. © 2010 Institute of Electrical and Electronics Engineers.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.approverLiu, Linda Y.
dc.contributor.mitauthorLiu, Linda Y.
dc.relation.journal2009 IEEE Sensors Conferenceen_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.orderedauthorsGoodin, Chris; Kala, Raju; Carrrillo, Alex; Liu, Linda Y.en
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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