Science Autonomy and Space Science: Application to the ExoMars Mission

A machine learning approach for analyzing data from the Mars Organic Molecule Analyzer (MOMA) instrument has been developed in order to improve accuracy and efficiency of this analysis serves as a case study use tools space missions. MOMA is part science payload aboard ExoMars rover, Rosalind Franklin, currently planned land on 2023. Most NASA robotic missions return only one thing: data. Remote planetary continue produce more mission ambitions capabilities grow, yet investigations are still limited by available bandwidth transmit back Earth. To maximize value each bit, instruments need be highly selective about which prioritized Earth, compression transmission full volume often not feasible. The fundamental goal enable concept autonomy , where perform selected onboard analyses then act upon those through self-adjustment tuning parameters. In paper, we discuss motivations, well related work We also present first step toward vision This proof-of-concept exercise aims develop tools, used support Martian operations mission. challenges limitations implementation, lessons learned approaches that could future