Advancing Autonomous Thermalling of Unmanned Aerial Gliders
As Unmanned Aerial Vehicles (UAVs) become more ubiquitous, a special class of UAVs known as Unmanned Aerial Gliders (UAGs) promises to offer more efficient flight by using atmospheric energy to remain afloat. In order to facilitate the usage of UAGs in various applications, researchers have developed algorithms which allow for autonomous flight of UAGs. The developed algorithms, however, still lag in performance as compared to piloted UAGs, and require an extensive amount of calibration upfront, making them difficult to implement on gliders of various sizes and properties. The proposed work will focus on improving the decision-making of the algorithms, allowing them to capture more of the surrounding atmospheric energy and improving overall performance. Furthermore, the algorithms will be adapted to simplify the implementation process, making it easier to implement.