Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Abstract

Autonomously guided parafoil systems can deliver supplies and aid to remote, geographically diverse locations, while providing important safety and logistical advantages over ground-based transportation methods. 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 critical for successful payload delivery due to uncertain atmospheric wind disturbances and underactuated parafoil dynamics. This paper presents a new online trajectory planning algorithm for autonomous parafoil guidance in complex terrain and wind environments. Through explicit, analytic modeling of the wind uncertainty, this algorithm, known as Chance Constrained Band-Limited Guidance (CC-BLG), addresses the limitations of existing parafoil guidance strategies by directly considering the possibility of future wind and terrain interaction during the trajectory planning process. Simulation experiments demonstrate that CC-BLG achieves significant improvements in both mean and worst-case landing accuracy relative to state-of-the-art approaches. Flight test experiments with a full-scale UltraFly parafoil system confirm that, by applying the method of analytic chance constraints presented in this work, the optimized CC-BLG algorithm can robustly execute collision avoidance and precision landings in a simulated Grand Canyon terrain.