Real-time obstacle avoidance for fixed-wing vehicles in complex environment
Rong Ma, Wen Ma, Xiaolong Chen, Jia Li · 2016
In this paper, we present a real-time obstacle avoidance method for fixed-wing unmanned aerial vehicles (UAVs) in complex environment. The Rapidly-exploring Random Tree(RRT) algorithm is used in this method. In order to adapt the RRT algorithm on fixed-wing platforms, we make extensions on it. The algorithm demonstrates very good performance in trajectory planning for fixed-wing vehicles in three-dimensional environment and dynamic environment. We analyze the algorithm theoretically and provide simulation results. We also demonstrate our method on a fixed-wing vehicle flying over a runway with multiple obstacles. The application of this method will greatly improve the survival ability of fixed-wing vehicles in complex environment. It is significant in elevation of autonomous level of UAV.