Robust, Explainable Autonomy for Scientific Icy Moon Operations (REASIMO)
Description
This effort aims to improve the science yield and robustness of a wide range of NASA missions by increasing the level of flight-qualifiable autonomy that can be applied to such operations.
Detailed example
Specifically, we are developing autonomy for onboard mission use that could detect, diagnose, and respond appropriately to anomalies (faults, failures degradations, or unexpected conditions) without the need to always drop into safe mode and call home.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Specifically, we are developing autonomy for onboard mission use that could detect, diagnose, and respond appropriately to anomalies (faults, failures degradations, or unexpected conditions) without the need to always drop into safe mode and call home.
Controls / human review
ATO: Not reported; PIA: Not published