Wind Uncertainty Modeling and Robust Trajectory Planning for Autonomous Parafoils

Abstract

A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into difficult, complex terrain. Robustness is a primary concern, given that environmental wind disturbances are often highly uncertain and time-varying. This paper presents a new online trajectory-planning algorithm that enables a large, autonomous parafoil with underactuated dynamics to robustly execute collision avoidance and precision landing on mapped terrain, even with significant wind uncertainties. This algorithm is designed to handle arbitrary initial altitudes, approach geometries, and terrain surfaces, and is robust to wind disturbances that may be highly dynamic throughout terminal approach. Real-time wind uncertainty modeling and classification are used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to future wind variation is efficiently maintained. The designed cost-to-go function enables selection of partial paths that intelligently trade off between current and reachable future states, while encouraging upwind landings. Simulation results demonstrate that this algorithm reduces the worst-case impact of wind disturbances relative to state-of-the-art approaches.