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MAARS: Machine learning-based Analytics for Automated Rover Systems

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dc.contributor.author Ono, Hiro
dc.contributor.author Rocthrock, Brandon
dc.contributor.author Otsu, Kyohei
dc.contributor.author Higa, Shoya
dc.contributor.author Iwashita, Yumi
dc.contributor.author Didier, Annie
dc.contributor.author Islam, Tanvir
dc.contributor.author Laporte, Christopher
dc.contributor.author Sun, Vivian
dc.contributor.author Stack, Kathryn
dc.contributor.author Sawoniewicz, Jacek
dc.contributor.author Daftry, Shreyansh
dc.contributor.author Timmaraju, Virisha
dc.contributor.author Sahnoune, Sami
dc.contributor.author Mattmann, Chris A
dc.date.accessioned 2021-11-30T23:07:32Z
dc.date.available 2021-11-30T23:07:32Z
dc.date.issued 2020-03-05
dc.identifier.citation 2020 IEEE Aerospace Conference, Big Sky, Montana, March 5-14, 2020
dc.identifier.clearanceno CL#20-1605
dc.identifier.uri http://hdl.handle.net/2014/52724
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2020
dc.title MAARS: Machine learning-based Analytics for Automated Rover Systems
dc.type Presentation


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