Unmanned Aerial Systems (UAS) integration to future airspace is one of the greatest challenges in Air Traffic Management. The use of UAS for covering wide areas implies the consideration of airspace restrictions and static and dynamic obstacle avoidance. This results in complex shapes that need to be partitioned adequately to ensure coverage. Another important element for consideration in the generation of safe and efficient trajectories of UAS is the wind field. Typically, in severe wind scenarios, wind is considered often a hazardous condition. However, recent studies show that proper identification of the wind field could be used to increase the energy efficiency of the mission. This paper presents a novel method of area decomposition and partition that ensures coverage by generating a triangular mesh to optimize the coverage in the presence of urban areas, airspace restrictions or even the presence of an obstacle. The waypoint sequencing considers the wind field in order to perform on-line adjustments to ensure energy gains or to minimize energy losses with the identified wind field. For this purpose, an innovative method for wind identification is proposed which analyses the statistical behavior of wind vector estimates in order to identify specific features and characterize given models. Given the design philosophy and architecture, this system can be integrated into next generation autonomous UAS flight management systems as part of the waypoint sequencing and trajectory optimization functions. A test case in the northSeattle area is presented, which is simulated using a 6DOF model with different wind scenarios which resulted into considerable energy gains either by heeding the wind field during the waypoint sequencing and during the mission execution. Results show that there is a significant improvement on the energy efficiency with an energy consumption reduced by 10% in the presence of wind.
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