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An Overview of AUV Algorithms Research and Testbed at the University of Michigan

dc.contributor.authorEustice, Ryan M.en_US
dc.contributor.authorBrown, Hunteren_US
dc.contributor.authorKim, Ayoungen_US
dc.date.accessioned2011-08-18T18:24:40Z
dc.date.available2011-08-18T18:24:40Z
dc.date.issued2008-10-13en_US
dc.identifier.citationEustice, R. M.; Brown, H.; Kim, A. (2008). "An Overview of AUV Algorithms Research and Testbed at the University of Michigan." Proceedings of the IEEE/OES Autonomous Underwater Vehicles Conference. <http://hdl.handle.net/2027.42/86058>en_US
dc.identifier.issn1522-3167en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/86058
dc.description.abstractThis paper provides a general overview of the autonomous underwater vehicle (AUV) research projects being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL's research thrust is centered around improving AUV autonomy via algorithmic advancements in sensor-driven perceptual feedback for environmentally-based real-time mapping, navigation, and control. In this paper we discuss our three major research areas of: (1) real-time visual simultaneous localization and mapping (SLAM); (2) cooperative multi-vehicle navigation; and (3) perception-driven control. Pursuant to these research objectives, PeRL has acquired and significantly modified two commercial off-the-shelf (COTS) Ocean-Server Technology, Inc. Iver2 AUV platforms to serve as a real-world engineering testbed for algorithm development and validation. Details of the design modification, and related research enabled by this integration effort, are discussed herein.en_US
dc.publisherIEEEen_US
dc.titleAn Overview of AUV Algorithms Research and Testbed at the University of Michiganen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelNaval Architecture and Marine Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Naval Architecture & Marine Engineering; Department of Mechanical Engineering.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/86058/1/reustice-15.pdf
dc.identifier.doi10.1109/AUV.2008.5290531en_US
dc.identifier.sourceProceedings of the IEEE/OES Autonomous Underwater Vehicles Conferenceen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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