An Intelligent Consumables Management System Development Framework based on Artificial Intelligence Techniques

The proposed innovation, called the Management of consumables Adaptive Execution, SynchronizaTion, Replanning/rescheduling, Optimization system (MAESTRO), would leverage the investment of NASA from originally funding the development of the Aurora Intelligent Scheduling framework and also leverage the previous NASA-funded Intelliface, to interface Aurora to diagnosis systems and extend it both to include more Course of Action (COA) development/planning and adaptive execution (i.e., executing the scheduled activities/procedures after scheduling). MAESTRO would be an open standards architecture and framework for the development of intelligent consumables management systems for autonomous and/or astronaut management of consumables. Each task (an abstract token) in a MAESTRO/Aurora schedule would be a procedure of several steps or actions that must be executed, and incorporating the Adaptive Execution capability of Intelliface (based on Open Source SimBionic) would allow the plans and schedules generated by MAESTRO to be adaptively executed. The Intelliface link to diagnosis systems allows the entire loop to be closed so that an autonomous or human-interfaced system can transition seamlessly between diagnosis, replanning, rescheduling, adaptive execution, etc. The generality of the proposed MAESTRO system will be proven, in Phase I, by using it to develop three separate consumable management systems for three separate applications using the same code base. Consumables management will be possible with significantly less skill and experience, less manpower, and reduced turnaround time. The multiple applications also show that MAESTRO is a general, open architecture.