Optimal flight trajectories through recursive thermal streets with uncertain climb rates

Abstract

The flight performance of Unmanned Aerial Vehicles (UAVs) has recently been attempted to be optimized in various static soaring applications. The optimal flight paths can be generated for specific scenarios where the climb rates of the rising air currents in the region are assumed to be deterministic. In order to improve these algorithmic approaches some degree of uncertainty yet needs to be allowed in describing the thermals. In this paper we consider the recursive thermal streets which can be modeled through Gaussian distributions with uncertain standard deviations. The UAV is assigned to climb several successive thermals characterizing these profiles and collect the required data which can then be used to estimate the location of the strongest thermals in the respective thermal streets. A more effective method for flight trajectory generation is hence developed in comparison to the tools based merely on remote detection data. Copyright © 2008 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.