Data Mining During Rover Traverse: From Images to Geologic Signatures

David R. Thompson, Trey Smith, and David Wettergreen
8th International Symposium on Artificial Intelligence, Robotics and Automation in Space, October, 2005.


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Abstract
Soon robotic explorers will be able to produce more scientific data than can be transmitted or interpreted efficiently. We present a method for characterizing geology during rover traverse using autonomous data analysis techniques. The strategy detects discrete geologic features in images; distributions of these features constitute a signature that correlates with the geology of each site. These numerical profiles reveal subtle trends and boundaries in geologic units that facilitate targeted sample selection and efficient data analysis. We demonstrate the system's use on field data collected during a field expedition to the Atacama Desert of Chile.

Keywords
Autonomous Science, Robotic Exploration, Autonomous Geology

Notes
Sponsor: NASA
Grant ID: NNG0-4GB66G, NAG5-12890
Associated Center(s) / Consortia: Field Robotics Center
Associated Project(s): Science Autonomy and Life in the Atacama
Number of pages: 8

Text Reference
David R. Thompson, Trey Smith, and David Wettergreen, "Data Mining During Rover Traverse: From Images to Geologic Signatures," 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space, October, 2005.

BibTeX Reference
@inproceedings{Thompson_2005_5114,
   author = "David R Thompson and Trey Smith and David Wettergreen",
   title = "Data Mining During Rover Traverse: From Images to Geologic Signatures",
   booktitle = "8th International Symposium on Artificial Intelligence, Robotics and Automation in Space",
   month = "October",
   year = "2005",
}