Collision-Avoidance Framework for Small Fixed-Wing Unmanned Aerial Vehicles

Collision avoidance is of vital importance to the autonomous flight of unmanned aerial vehicles (UAV). This especially is true for small UAVs flying at low heights, which usually encounter a large number of mostly static obstacles. Due to a limited knowledge of the environment and small computing power, collision-avoidance algorithms need to rely on little information while being computationally efficient. Guidance laws are one way of tackling such difficulties. The remaining design parameters are determined considering convergence and performance properties of the closed guidance loop. Then, the guidance framework is developed in terms of a constrained optimization problem that can avoid multiple obstacles simultaneously while incorporating other mission objectives. Although avoiding collisions is often crucial to mission success, it is rarely the only or primary objective. This reveals the need for an integrated approach simultaneously considering a given mission objective and collision avoidance with an arbitrary number of potentially moving obstacles.