Automated global feature analyzer - A driver for tier-scalable reconnaissance

Wolfgang Fink, Ankur Datta, James M. Dohm, Mark A. Tarbell, Farrah M. Jobling, Roberto Furfaro, Jeffrey S. Kargel, Dirk Schulze-Makuch, Victor R. Baker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

For the purposes of space flight, reconnaissance field geologists have trained to become astronauts. However, the initial forays to Mars and other planetary bodies have been done by purely robotic craft. Therefore, training and equipping a robotic craft with the sensory and cognitive capabilities of a field geologist to form a science craft is a necessary prerequisite. Numerous steps are necessary in order for a science craft to be able to map, analyze, and characterize a geologic field site, as well as effectively formulate working hypotheses. We report on the continued development of the integrated software system AGFA: Automated Global Feature Analyzer

Original languageEnglish (US)
Title of host publication2008 IEEE Aerospace Conference, AC
DOIs
StatePublished - Aug 19 2008
Event2008 IEEE Aerospace Conference, AC - Big Sky, MT, United States
Duration: Mar 1 2008Mar 8 2008

Publication series

NameIEEE Aerospace Conference Proceedings
ISSN (Print)1095-323X

Other

Other2008 IEEE Aerospace Conference, AC
CountryUnited States
CityBig Sky, MT
Period3/1/083/8/08

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science

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    Fink, W., Datta, A., Dohm, J. M., Tarbell, M. A., Jobling, F. M., Furfaro, R., Kargel, J. S., Schulze-Makuch, D., & Baker, V. R. (2008). Automated global feature analyzer - A driver for tier-scalable reconnaissance. In 2008 IEEE Aerospace Conference, AC [4526422] (IEEE Aerospace Conference Proceedings). https://doi.org/10.1109/AERO.2008.4526422