Tai, Ann — National Aeronautics and Space Administration SBIR Phase I: H6

Description

<p>While automation technologies advance faster than ever, gaps of resilience capabilities between autonomous and human-operated systems have not yet been filled in proportion. &nbsp;Accordingly, ATanalytics, in collaboration with The Center for Reliability and Resilience Engineering (CRRE) of The B. John Garrick Institute for the Risk Sciences at UCLA proposes to develop a methodology and toolkit for assured resilience of autonomous systems (ARAS). &nbsp;The central part of the ARAS methodology consists of two gap fillers: (1) an ontology-driven database supporting resilience engineering activities and resilience modeling, and (2) a resilience assessment and optimization employing a Hybrid Causal Logic (HCL) based software platform for resilience engineering support. &nbsp;The database includes resilience engineering principles, archetype mission scenarios, and metric meta models. &nbsp;With the HCL-based resilience assessor, a high-level model at the top layer enables resilience metrics to be defined at the mission-scenario level (or CONOPS level) and be subsequently mapped to the lower-level models to capture system specifics. &nbsp;Our innovation will be a significant step forward to resilience engineering standardization since (i) the database (a knowledge hub) and resilience models will be onboard resources enabling both design-for-resilience and onboard decision making for resilience assurance, and (ii) the HCL metrics-in-the-loop methodology is inherently generalizable for different levels of system abstraction, life-cycle, and mission phases.</p>