Long Distance/Duration Trajectory Optimization for

This paper presents a system for autonomous soaring flight by small and micro unin-habited aerial vehicles. It combines a prediction of wind field with a trajectory planner, a decision-making block, a low-level flight controller and sensors such as Global Positioning System and air data sensors to enable exploitation of atmospheric energy using thermals, wave, and orographic lift or dynamic soaring. The major focus of this research is on exploiting orographic (i.e. slope or ridge) lift to enable long duration, long distance flights by a small autonomous uninhabited aerial vehicle (UAV). This paper presents a methodology to generate optimal trajectories that utilize the vertical component of wind to enable flights that would otherwise be impossible given the performance constraints of the UAV. A point mass model is used to model the aircraft and a polynomial function which includes both horizontal and vertical variations in wind speed is used to model the wind field. Both vehicle kinematic and minimum altitude constraints are included. Results for a test case (crossing the Altoona Gap in Pennsylvania’s Bald Eagle Ridge) are presented for both minimum time and maximum final energy trajectories. I