Stottler Henke is extending our prior work to develop artificial intelligence (AI) Reasoning Modules for planning, scheduling, characterization, machine learning, and fault detection/diagnosis/reconfiguration for spacecraft and their subsystems. Each is able to operate in standalone fashion or be easily integrated with one another to execute in a variety of computational environments, including in highly distributed situations. We will integrate our existing AI Modules within NASA’s core Flight System (cFS) so that they can be used (through cFS) on a wide variety of spacecraft, from large manned vehicles to small scientific instruments. We will also integrate the AI Modules on Montana State University’s (MSU) RadPC (radiation tolerant processing CPUs) in an experiment onboard the International Space Station (ISS).

This will speed up the maturation of MSU’s RadPC, replacing $200,000 RAD750 radiation hardened processing with equivalent processing power in $100 FPGA chips using soft-CPUs, quadruple redundancy, and FPGA reconfiguration for seamless recovery, achieving 3 orders of magnitude reduction in cost as well as significantly reduced CPU electrical power. The ISS experiment will fly for six months and feature two RadPC boards, one of which will be utilizing the full suite of AI Modules to monitor, detect, diagnose, and recover the other RadPC board as well as its own, providing an inflight demonstration for both RadPC and for the AI Modules.
The modules will utilize cFS’s Software messaging Bus (SB) and the networking version (SBN) to provide the integration mechanism for either local or distributed applications, such as a specific spacecraft mission potentially utilizing the AI Scheduler merely by sending it tasks, resources, and constraints in the defined messaging format across the SB or SBN, while another application could use a different AI Module; Characterization. A third might use all of the AI Reasoning applications.