The Research On Autonomous Path Planning Technology And Simulation Of UAVs

It is an important field of unmanned air vehicles (UAVs) research that UAVs in an unknown environment can adaptively online-plan path in real time. It is impossible to get accurate information on global environment when UAVs is flighting in actual flight environment. So it can not get an effective global planning path in the case of off-line. As the sensing range of UAVs' sensors is very limited, it can not reach a global perspective. Path planning can only use the local environmental information detected in real-time. This papar designs an autonomous path planning method of UAV refer on prediction theory and artificial intelligence decision-making methods, and effectively integrate the rolling optimization and feedback mechanisms. Not only to ensure the optimality of the global route, But also to ensure the local route to avoid obstacles in real time. And it makes UAVs to better adapt to environmental changes. Therefore, this result of this research will particularly play the important role in UAVs combating.The paper describes briefly the research background, development and key technologies of the path planning firstly, and the threats factors of path planning and the constraints of UAVs' own are analyzed and modeled, it is the foundation of the consider of threats in path planning algorithm. Then the method of global path planning based on particle swarm optimization (PSO) algorithm is researched and simulated, and the method of local path planning based on detection window of UAVs are researched and designed. The method completes the obstacle avoidance and the local dynamic path planning through detecting real-time UAV flight environment, continuously updating environmental information and forecasting the movement trend of dynamic obstacles, by the UAVs' own airborne sensors as detection window.The key of this paper is to propose a autonomous path planning technology of to achieve independently to effects of both security avoid obstacle and path optimization. The method of global path planning based on PSO algorithm and the method of local path planning based on detection window are reasonable combined with global and local balance strategy. By the reference factors make the exact decision on come around back to the original reference path or give up the original reference path and re-plan the global path, so plan the best path of UAVs', and improve the adaptive of the path planning of UAVs. The process of this method mimics completely the process of aircraft pilots avoiding the obstacle. It makes the method route planning of UAVs be more intelligent. UAVs can plan the best path by their own under the case of no one intervention, get rid of dependence on human driving and directions. It will greatly enhance the success rate of the long-range sudden strike of the aircraft, it has the important practical value of improving the combat effectiveness of China's national defense science and technology.