Sense and collision avoidance of Unmanned Aerial Vehicles using geometric guidance and flatness approaches

This paper describes the development of a Sense and Avoid (S&A) algorithm that can ensure an Unmanned Aerial Vehicle (UAV) being able to avoid collisions autonomously. Firstly, the Closest Point of Approach (CPA) can predict the conflict. Secondly, the developed path planner generates the feasible path using differential geometric guidance and flatness techniques, where the constraints of UAV dynamics are considered. The effectiveness of the developed scheme is demonstrated by flight tests carried out at the Marinvent© Flight Simulator.