Robot Reliability Using Fuzzy Fault Trees and Markov Models

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dc.citation.conferenceDate1996en_US
dc.citation.conferenceNameSPIE Conference on Sensor Fusion and Distributed Robotic Agentsen_US
dc.citation.firstpage73en_US
dc.citation.lastpage91en_US
dc.citation.locationBoston, MAen_US
dc.contributor.authorLeuschen, Martin L.en_US
dc.contributor.authorWalker, Ian D.en_US
dc.contributor.authorCavallaro, Joseph R.en_US
dc.contributor.orgCenter for Multimedia Communicationen_US
dc.date.accessioned2012-05-18T17:18:14Zen_US
dc.date.available2012-05-18T17:18:14Zen_US
dc.date.issued1996-11-01en_US
dc.description.abstractRobot reliability has become an increasingly important issue in the last few years, in part due to the increased application of robots in hazardous and unstructured environments. However, much of this work leads to complex and nonintuitive analysis, which results in many techniques being impractical due to computational complexity or lack of appropriately complex models for the manipulator. In this paper, we will consider the application of notions and techniques from fuzzy logic, fault trees, and Markov modeling to robot fault tolerance. Fuzzy logic lends itself to quantitative reliability calculations in robotics. The crisp failure rates which are usually used are not actually known, while fuzzy logic, due to its ability to work with the actual approximate (fuzzy) failure rates available during the design process, avoids making too many unwarranted assumptions. Fault trees are a standard reliability tool that can easily assimilate fuzzy logic. Markov modeling allows evaluation of multiple failure modes simultaneously, and is thus an appropriate method of modeling failures in redundant robotic systems. However, no method of applying fuzzy logic to Markov models was known to the authors. This opens up the possibility of new techniques for reliability using Markov modeling and fuzzy logic techniques, which are developed in this paper.en_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipSandia National Laboratoryen_US
dc.identifier.citationM. L. Leuschen, I. D. Walker and J. R. Cavallaro, "Robot Reliability Using Fuzzy Fault Trees and Markov Models," 1996.en_US
dc.identifier.doihttp://dx.doi.org/10.1117/12.256340en_US
dc.identifier.otherhttp://scholar.google.com/scholar?cluster=2268328142733824149&hl=en&as_sdt=0,44en_US
dc.identifier.urihttps://hdl.handle.net/1911/64160en_US
dc.language.isoengen_US
dc.publisherSPIEen_US
dc.subjectFault Toleranceen_US
dc.subjectRoboticsen_US
dc.subjectFuzzy Logicen_US
dc.subjectReliabilityen_US
dc.subjectFault Treesen_US
dc.subjectMarkov Modelsen_US
dc.titleRobot Reliability Using Fuzzy Fault Trees and Markov Modelsen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
dc.type.dcmiTexten_US
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