Robot Reliability Through Fuzzy Markov Models

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dc.citation.conferenceDate1998en_US
dc.citation.conferenceNameIEEE Annual Reliability and Maintainability Symposiumen_US
dc.citation.firstpage209
dc.citation.lastpage214
dc.citation.locationAnaheim, CAen_US
dc.contributor.authorLeuschen, Martin L.
dc.contributor.authorWalker, Ian D.
dc.contributor.authorCavallaro, Joseph R.
dc.contributor.orgCenter for Multimedia Communicationen_US
dc.date.accessioned2012-07-03T15:34:25Z
dc.date.available2012-07-03T15:34:25Z
dc.date.issued1998-01-01eng
dc.description.abstractIn the past few years, new applications of robots have increased the importance of robotic reliability and fault tolerance. Standard approaches of reliability engineering rely on the probability model, which is often inappropriate for this task due to a lack of sufficient probabilistic information during the design and prototyping phases. Fuzzy logic offers an alternative to the probability paradigm, possibility, that is much more appropriate to reliability in the robotic context.en_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNASAen_US
dc.description.sponsorshipOffice of Naval Researchen_US
dc.description.sponsorshipSandia National Laboratoryen_US
dc.identifier.citationM. L. Leuschen, I. D. Walker and J. R. Cavallaro, "Robot Reliability Through Fuzzy Markov Models," 1998.*
dc.identifier.doihttp://dx.doi.org/10.1109/RAMS.1998.653739en_US
dc.identifier.urihttps://hdl.handle.net/1911/64355
dc.language.isoengen
dc.publisherIEEEen_US
dc.subjectFault Treesen_US
dc.subjectMarkov modelingen_US
dc.subjectRoboticsen_US
dc.subjectInterval arithmeticen_US
dc.subjectFuzzy setsen_US
dc.titleRobot Reliability Through Fuzzy Markov Modelsen_US
dc.typeConference paperen_US
dc.type.dcmiTexten
dc.type.dcmiTexten_US
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