Toward Resilient Spacecraft: Artificially Intelligent Reasoning for Diagnosing Safe Modes
Project Description
This research will develop a proof-of-concept prototype for an intelligent and explainable reasoning system on-board, which is capable of diagnosis and decision making in real-time. The framework will leverage classification systems such as Neural Networks (NN) and various uncertainty processing methods such as Dempster–Shafer theory (DST) to make use of low level data as a way to inform higher level reasoning system to generate on-board information at an abstract level which is human readable. We will look specifically at implementing our proof-of-concept as a way to diagnose spacecraft safe-mode events, in an attempt to disambiguate non-urgent anomalous safe mode events from more urgent safe-mode events which require a sunward burn maneuver.
More »Anticipated Benefits
It is our objective to use this work as a basis for investigation of true functional resiliency, serving as a catalyst and platform for continuing research for spacecraft autonomy. Specifically, this research will help resolve the restrictions that come with reduced or infrequent ground control communication, especially in critical anomalous situations. Moreover, this research is promising in pushing the frontier of accessible deep space exploration, currently held back by necessary earth proximity for ground control communication.
More »Project Library
Primary U.S. Work Locations and Key Partners
| Organizations Performing Work | Role | Type | Location |
|---|---|---|---|
Goddard Space Flight Center
(GSFC)
|
Lead Organization | NASA Center | Greenbelt, Maryland |
Primary U.S. Work Locations
-
Maryland
