Autonomous onboard traverse science system

Castano, R.; Judd, M.; Estlin, T.; Anderson, R. C.; Scharenbroich, L.; Song, L.; Gaines, D.; Fisher, F.; Mazzoni, D.; Castano, A.

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