UAS Collision Avoidance, Navigation, and Target Assignment in a Congested Airspace Using Fuzzy Logic
Brandon Cook, Timothy J. Arnett, Brett Rich, Elad H. Kivelevitch · 2015
1 As Unmanned Aerial Vehicle (UAVs) applications continue to proliferate, solutions to congested airspace control will need to be studied. This problem can be broken down into smaller problems such as collision avoidance, waypoint navigation, vehicle priority assignment, and target assignment. Moreover, main research challenges include situational awareness and decision making in an uncertain, time-critical, spatio-temporal environment. The goal of this study is the creation, implementation, and integration of these smaller algorithms into an overarching simulated airspace, with multiple UAVs and targets. Additionally, the simulation environment created should be robust enough to easily employ different algorithms for each of these subsystems. Fuzzy Logic will be used throughout the scope of this project to show the robustness of Fuzzy Logic in these capacities. It was found that the collision avoidance algorithm is 100% collision free for the Static, Dynamic, and Clustered simulations, for both Priority and Non-Priority cases (all cases) over a span of 7,509 flight hours.