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Title: Machine learning challenges in Mars rover traverse science
Authors: Castano, R.
Judd, M.
Anderson, R. C.
Estlin, T.
Issue Date: 21-Aug-2003
Citation: 2003 ICML Workshop on Machine Learning Technologies for Autonomous Space
Washington D.C., USA
Abstract: The successful implementation of machine learning in autonomous rover traverse science requires addressing challenges that range from the analytical technical realm, to the fuzzy, philosophical domain of entrenched belief systems within scientists and mission managers.
Appears in Collections:JPL TRS 1992+

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