A heuristic search algorithm for maneuvering of UAVs across dense thermal areas

Abstract

In order to ensure that an aircraft has the potential to meet the assigned performance requirements which are often mission specific, the particular aerodynamic demands involved must be taken into account during the aircraft design phase. Once the design is completed and the parts of the aircraft are assembled, carefully chosen soaring strategies prove an additional source of flight performance enhancements which in turn provide further feedback for designers. As such, there has been considerable interest in modern glider design and soaring flight during the last few decades. The Unmanned Aerial Vehicles (UAVs) designed for soaring flight currently demand more efficient soaring strategies that would allow them to cover larger flight distances, possibly even faster. In this paper we discuss the maneuvering of a glider UAV across dense thermal regions. We present a problem scenario where the objective is to climb the assigned thermals in the area of interest and complete the flight mission in minimum time. Our solution methodology is based on dividing the maneuvering area into main sectors and applying a minimal spanning tree algorithm to cover the set of thermals detected in each sector. A parallel savings based heuristic is included in order to improve the path decision process while a maximum distance constraint is also incorporated. An adaptive control scheme is developed for the linear UAV model used in simulations through which the performance of the proposed near-optimal soaring algorithm is verified.