Automated Motion Libraries for Enhanced Data-Driven Intelligence (FY19 Technical Report)

Abstract

Hypersonic vehicles hold great promise for a range of applications. However, they are subject to complex dynamics including high temperatures, thick boundary layers, and gas reaction effects. These coupled nonlinear dynamics make vehicle control and planning especially challenging. Specifically, it is very difficult to rapidly predict the vehicle response to control inputs and time-varying conditions. While reduced order models have shown great promise for predicting behavior in a more rapid manner, these techniques still require powerful computers and several simplifying assumptions. As a result, we currently lack the ability to rapidly plan (or re-plan) the trajectories of hypersonic vehicles.