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Autonomous onboard traverse science system

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dc.contributor.author Castano, R. en_US
dc.contributor.author Judd, M. en_US
dc.contributor.author Estlin, T. en_US
dc.contributor.author Anderson, R. C. en_US
dc.contributor.author Scharenbroich, L. en_US
dc.contributor.author Song, L. en_US
dc.contributor.author Gaines, D. en_US
dc.contributor.author Fisher, F. en_US
dc.contributor.author Mazzoni, D. en_US
dc.contributor.author Castano, A. en_US
dc.date.accessioned 2004-09-16T23:56:11Z
dc.date.available 2004-09-16T23:56:11Z
dc.date.issued 2004-03-06 en_US
dc.identifier.citation IEEE Aerospace 2004 en_US
dc.identifier.citation Big Sky, MT, USA en_US
dc.identifier.clearanceno 03-2863 en_US
dc.identifier.uri http://hdl.handle.net/2014/7968
dc.description.abstract This paper provides a brief overview of the entire OASIS system and how it analyzes one type of data - grayscale images taken by the rover for engineering and hazard avoidance purposes. en_US
dc.format.extent 3250897 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other OASIS machine learning onboard science en_US
dc.title Autonomous onboard traverse science system en_US


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