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AGU: Journal of Geophysical Research, Biogeosciences

 

Keywords

  • robotic exploration
  • astrobiology
  • science autonomy

Index Terms

  • 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
Abstract
Cited By (3)
 

Abstract

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, G04S03, 23 PP., 2007
doi:10.1029/2006JG000315

Life in the Atacama: Science autonomy for improving data quality

Trey Smith

Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

David R. Thompson

Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

David S. Wettergreen

Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

Nathalie A. Cabrol

NASA Ames Research Center, Moffett Field, California, USA

Kimberley A. Warren-Rhodes

NASA Ames Research Center, Moffett Field, California, USA

Shmuel J. Weinstein

Molecular Biosensor and Imaging Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

“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.

Received 19 September 2006; accepted 6 August 2007; published 7 December 2007.

Citation: Smith, T., D. R. Thompson, D. S. Wettergreen, N. A. Cabrol, K. A. Warren-Rhodes, and S. J. Weinstein (2007), Life in the Atacama: Science autonomy for improving data quality, J. Geophys. Res., 112, G04S03, doi:10.1029/2006JG000315.

Cited By

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