Statistics – Computation
Scientific paper
Dec 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007jgrg..11204s03s&link_type=abstract
Journal of Geophysical Research, Volume 112, Issue G4, CiteID G04S03
Statistics
Computation
1
Biogeosciences: Astrobiology And Extraterrestrial Materials, Biogeosciences: Life In Extreme Environments, Computational Geophysics: Data Analysis: Algorithms And Implementation, Computational Geophysics: Neural Networks, Fuzzy Logic, Machine Learning, Exploration Geophysics: Instruments And Techniques
Scientific paper
``Science autonomy'' refers to exploration robotics technologies involving onboard science analysis of collected data. These techniques enable a rover to make adaptive decisions about which measurements to collect and transmit. Science autonomy can compensate for limited communications bandwidth by ensuring that planetary scientists receive those images and spectra that best meet mission goals. Here, we present the results of autonomous science experiments performed in the Atacama Desert of Chile during the Life in the Atacama (LITA) rover field campaign. We aim to provide an overview of autonomous science principles and examine their integration into the LITA operations strategy. We present experiments in four specific autonomous science domains: (1) autonomously responding to evidence of life with more detailed measurements; (2) rock detection for site profiling and selective data return; (3) tactical replanning to efficiently map the distribution of life; (4) detecting novel images and geologic unit boundaries in image sequences. In each of these domains we demonstrate improvements in the quality of returned data through autonomous analysis of imagery.
Cabrol Nathalie A.
Smith Trey
Thompson David R.
Warren-Rhodes Kimberley A.
Weinstein Shmuel J.
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