Machine Learning for Spacecraft at Europa: Enabling Faster Exploration in a High-Radiation Environment is coming at 01/22/2020 - 1:00pm
Gleeson 200 Wed, 01/22/2020 - 1:00pm Kiri L. Wagstaff Senior Instructor, Oregon State University, Principal Researcher, NASA Jet Propulsion Laboratory Abstract: Upcoming missions to remote destinations like Jupiter’s moon Europa will operate at extreme distances from the Earth where direct human oversight is impossible. The combination of extreme distance, limited lifetime due to high radiation, and limited data downlink creates an urgent need for reliable autonomous operations. Machine learning can help by analyzing data for features of interest as it is collected. Data with positive detections can be marked for high priority downlink to Earth for mission planning. For Europa, such features include active icy plumes and unusual surface mineral deposits. This talk describes data analysis and machine learning methods that can operate onboard to increase the rate of exploration and discovery. I will also describe how to assess algorithm radiation sensitivity to determine which ones are sufficiently robust for mission use. Bio: Read more: https://eecs.oregonstate.edu/colloquium/machine-learning-spacecraft-euro... [1] [1] https://eecs.oregonstate.edu/colloquium/machine-learning-spacecraft-europa-enabling-faster-exploration-high-radiation-environment
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