Pose and wind estimation for autonomous parafoils

Abstract

This dissertation presents two contributions to the development of autonomous aerial delivery systems (ADSs), both of which advance the prospect of enabling an ADS to land on a moving platform, such as the deck of a ship at sea. The first contribution addresses the problem of estimating the target’s position and velocity. A novel, dual-rate estimation algorithm based on Unscented Kalman filtering allows the ADS to use visual measurements from a fixed monocular sensor to estimate the target’s motion even when the ADS’s swinging motion in flight causes the target to be out of view. The second contribution addresses the problem of planning a landing trajectory considering winds in the vertical air mass between the target’s height and the ADS’s altitude. A wind model that assumes a logarithmic relationship between horizontal wind velocity and height in the air mass enables the ADS’s guidance algorithm to plan a valid landing trajectory in the presence of these winds. This dissertation contains simulation results for the visual estimation algorithm that show that estimation errors are minimal after estimator convergence. Flight test results indicate that the wind modeling algorithm was useful for computing landing trajectories.