Risk-Aware Navigation and Guidance for Resilience (RANGR)

Because traditional methods for assessing risk in UAS operations with the National Airspace (NAS) are unavailable, alternatives must be sought. As such, the work detailed within this proposal can be split into two significant parts. The first part is the identification of information sources, both open and commercial, from which databases of inferred population-based risk can be generated. The second part is the Risk-Aware Navigation and Guidance for Resilience (RANGR) algorithm. RANGR will take the information from the generated databases and identify temporal and spatial patterns within the population-based risk and develop a finite state machine (FSM) that describes the likely location and distribution of the population of a given area at a given time. For each state within the FSM, a collection of constraints called the hierarchical constraint set (HCS) will be developed that describe the different levels and locations of risk associated with that state. The HCS describes the risk as convex polytopes using a linear matrix inequality (LMI) formulation. Using these constraints, mission parameters, and a prescribed maximum level of risk, optimal paths, and their underlying rationale, will be generated within the risk space and provided to a user for selection and execution.