AI-ML and space exploration at NASA - Victoria Da Poian
Big Data and AI Toronto 2020 - Main stage
Speaker: Victoria Da Poian, Aerospace Engineer @ NASA
The majority of planetary missions return only one thing: data. As space exploration missions’ ambitions keeps evolving as well as the development of very mature instruments maximizing the value of each bit sent back to Earth, Science Autonomy -- the ability for science instruments to autonomously tune, operate, analyze, and direct themselves to optimize science return -- is necessary. Recent developments have demonstrated the tremendous potential of robotic explorers for planetary exploration and for other extreme environments. NASA believe that science autonomy has the potential to be as important as robotic autonomy (e.g., roving terrain) in improving the science potential of these missions because it directly optimizes the returned data. At NASA Goddard Space Flight center, we are developing a first step toward this vision: a ML approach for analyzing science data from the Mars Organic Molecule Analyzer (MOMA) instrument, which will land on Mars within the ExoMars rover Rosalind Franklin in 2023 to search for molecular biosignatures that might reveal signs of ancient martian life.
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