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The Human Spacecraft Cognitive Computing project will focus on integrating the power of cognitive computing into system health management and task planning for vehicle maintenance, particularly for the uncrewed phase of the planned Deep Space Gateway (DSG) operations. IBM’s Watson is a massive technology development that is capable of drawing conclusions from data using a machine learning technique called cognitive computing. Its emphasis on natural language processing and potential applications to system health management and procedure completion makes Watson an exciting technology platform with several interesting integration points into this project. Specifically, this project will focus on further exploring cognitive technologies and their incorporation into a smart spacecraft system. A demonstration of system health management (SHM) and simple procedure following to correct a fault or a set of faults in an integrated spacecraft simulation will result, leveraging the iPAS (Integrated Power and Avionics System) testbed and the Modular Autonomous Systems Technology framework, both developed at Johnson Space Center. Minimum success will be a demonstration of fault detection in the AES Modular Power System (AMPS) subsystem. Full success will be defined as a demonstration of fault detection, isolation and recovery for an integrated fault involving both power and ECLSS subsystems.
Future exploration missions are going to require complex human spacecraft to provide more autonomy from ground control both when humans are on board and when the spacecraft is uncrewed. This will require a new paradigm for designing these spacecraft, starting from the requirements and system design. One of the many facets of creating this autonomous system is to develop on board intelligence that can handle fault detection, isolation, and recovery, procedure selection and execution, maintenance, and planning. This project was created to explore a promising class of artificial intelligence called cognitive computing to understand its potential benefits (and drawbacks) for incorporation into a smart spacecraft system.
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