Sampling based collision avoidance for UAVs
We present the design and implementation of a path planning algorithm for Unmanned Aerial Vehicles (UAVs) to avoid collisions with other aircraft. The aircraft are indifferent to the UAV. A sampling based method is developed to generate the avoidance path. The UAV's closed loop system is used to simulate the trajectory in collision check used in path planning. The generated path is then checked against updated states of the UAV and obstacle aircraft, and a new path will be planned if the original one leads to a collision. The algorithm is validated in Hardware In the Loop simulation (HIL) and real flight experiments. The paper shows that the algorithm is able to generate paths for the UAV to avoid obstacles of different numbers, approaching angles, and speeds.
2016 American Control Conference (ACC)