%0 Journal Article %A LIU Jia %A QIN Xiaolin %A XU Yang %A ZHANG Lige %T On-line path planning method of fixed-wing unmanned aerial vehicle %D 2019 %R 10.11772/j.issn.1001-9081.2019050863 %J Journal of Computer Applications %P 3522-3527 %V 39 %N 12 %X By the combination of fuzzy particle swarm optimization algorithm based on receding horizon control and improved artificial potential field, an on-line path planning method for achieving fixed-wing Unmanned Aerial Vehicle (UAV) path planning in uncertain environment was proposed. Firstly, the minimum circumscribed circle fitting was performed on the convex polygonal obstacles. Then, aiming at the static obstacles, the path planning problem was transformed into a series of on-line sub-problems in the time domain window, and the fuzzy particle swarm algorithm was applied to optimize and solve the sub-problems in real time, realizing the static obstacle avoidance. When there were dynamic obstacles in the environment, the improved artificial potential field was used to accomplish the dynamic obstacle avoidance by adjusting the path. In order to meet the dynamic constraints of fixed-wing UAV, a collision detection method for fixed-wing UAV was proposed to judge whether the obstacles were real threat sources or not in advance and reduce the flight cost by decreasing the turning frequency and range. The simulation results show that, the proposed method can effectively improve the planning speed, stability and real-time obstacle avoidance ability of fixed-wing UAV path planning, and it overcomes the shortcoming of easy to falling into local optimum in traditional artificial potential field method. %U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2019050863