The drill of the Rosalind Franklin rover as a science instrument to characterize the Martian subsurface
- Paper number
IAC-24,A3,3A,4,x85365
- Author
Dr. Lorenzo Rossi, INAF-IAPS, Italy
- Coauthor
Dr. Francesca Altieri, INAF, Italy
- Coauthor
Dr. Alessandro Frigeri, INAF - Istituto Nazionale di AstroFisica, Italy
- Coauthor
Dr. Simone De Angelis, INAF-IAPS, Italy
- Coauthor
Dr. Maria Cristina De Sanctis, INAF, Italy
- Coauthor
Dr. Marco Ferrari, INAF-IAPS, Italy
- Coauthor
Dr. Sergio Fonte, INAF-IAPS, Italy
- Coauthor
Dr. Michelangelo Formisano, INAF-IAPS, Italy
- Coauthor
Mr. Matteo Paolo Clemente, Altec S.p.A., Italy
- Coauthor
Dr. Lucia Cordeschi, Altec S.p.A., Italy
- Coauthor
Mr. Andrea Merlo, Thales Alenia Space Italia (TAS-I), Italy
- Coauthor
Mr. Luc Joudrier, European Space Agency (ESA), The Netherlands
- Coauthor
Dr. Elliot Sefton-Nash, European Space Agency (ESA), The Netherlands
- Coauthor
Mr. Jorge L. Vago, European Space Agency (ESA), The Netherlands
- Year
2024
- Abstract
Rosalind Franklin, set to be launched in 2028, will be the first Mars rover capable of reaching a depth of 2 m with its drill. The drill is designed to collect subsurface (or surface) samples and deliver them to a suite of analytical instruments that will characterize them and look for the presence of possible biomarkers\:[1]. In addition to sample-studying instruments, the rover will also provide context information about the shallow subsurface environment the sample is taken from. The subsurface-characterizing instruments include CLUPI, a close-up imager, WISDOM, a ground-penetrating radar, and Ma\_MISS, a miniaturized reflectance spectrometer embedded in the drill tip. Ma\_MISS will perform spectral measurements on the wall of the just-drilled borehole, providing information about the mineralogy and stratigraphy of the drilling site\:[2].\smallskip To improve and extend the characterization of the subsurface environment, the rover instruments' measurements can be complemented with information about the mechanical properties of the rocks and soil the drill bores through. While there is no dedicated instrument for directly assessing mechanical properties, the drill itself can be used for this purpose: useful information can be retrieved from drill telemetry data using suitable analysis techniques.\smallskip We are thus devising methods to extract science information about the mechanical properties of the Martian subsurface from drill telemetry data. The techniques we are developing include a combination of feature engineering and various machine learning algorithms. For example, some unsupervised clustering algorithms are proving effective at telling apart stratigraphy layers with different properties, without requiring any {\it a-priori} knowledge. We have also developed a supervised classification model based on a 1D Convolutional Neural Network trained on data coming from drilling tests performed with the rover's GTM (Ground Test Model). This classifier achieves very high accuracy on the GTM dataset (98\% classification accuracy on the test set), but more drilling tests and larger datasets are needed to extend it and assess its performance on broader classification tasks.\smallskip We are also developing an instrumented laboratory drill to start accumulating more data quickly and independently from the GTM test schedule. The dataset this drill will provide will aid the development and validation of improved data analysis techniques, that could then be adapted to the rover’s drill system.\bigskip {\bf Acknowledgements:\;}This work is supported by the ASI Grant ASI-INAF n.\,2023–3–HH.0.\bigskip {\bf References:\;}{\bf [1]}\:Vago et al. (2017) Astrobiology\,17,471.\;{\bf [2]}\:De Sanctis et al. (2022) PSJ\,3:142.- Abstract document
- Manuscript document
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