一种三维环境中的无人机多路径规划方法 -- 西北工业大学,2014,32(3):412-416
论文:2014,Vol:32,Issue(3):412-416
引用本文:
刘洋, 章卫国, 李广文, 史静平. 一种三维环境中的无人机多路径规划方法[J]. 西北工业大学
Liu Yang, Zhang Weiguo, Li Guangwen, Shi Jingping. A Multi-Path Planning Method for Unmanned Aerial Vehicle (UAV) in 3D Environment[J]. Northwestern polytechnical university

一种三维环境中的无人机多路径规划方法
刘洋, 章卫国, 李广文, 史静平
西北工业大学 自动化学院, 陕西 西安 710129
摘要:
为了解决三维环境中的无人机多路径规划问题,提出了一种基于改进概率地图的多目标蚁群算法。在构建地图时为了增加窄通道中的采样点数量,改进了概率地图法的采样策略,将落在威胁上的采样点移动到自由空间中,可以更好地覆盖规划环境。为了使蚁群算法可以得到多个解,提出了一种多目标蚁群算法。通过引入Pareto解集,播撒不同种类的信息素,使蚁群算法可以同时优化路径长度和威胁大小2个目标,并能得到一组非支配解,有利于决策者选择合适的路径。仿真结果表明,改进的概率地图法可以更好地覆盖规划环境,多目标蚁群算法可以得到一组解,并能收敛到最终解集。
关键词:    无人机    路径规划    概率地图    多目标蚁群算法    三维环境   
A Multi-Path Planning Method for Unmanned Aerial Vehicle (UAV) in 3D Environment
Liu Yang, Zhang Weiguo, Li Guangwen, Shi Jingping
Department of Automatic Control, Northwestern Polytechnical University, Xi'an 710129, China
Abstract:
In order to solve the problems existing in the multi-path planning for UAV in the 3D environment, we improve the probability roadmap method (PRM) by moving the sampling points to increase their number in their narrow passage so that the PRM can better serve the multi-path planning environment. Then we propose the multi-objective ant colony algorithm (MACA) based on the PRM and apply it to the multi-path planning of the UAV. The MACA can optimize the path length and threat size of the UAV at the same time by updating their pheromones, thus obtaining a set of non-dominant solutions for the decision maker to select appropriate paths. To verify the effective-ness of the MACA, we simulate the multi-path planning environment as shown in Fig. 1; the simulation results, given in Fig.4 and 5 and Tables 1 and 2, and their analysis show preliminarily that our MACA based on PRM serves the 3D multi-path planning environment very well and can obtain a set of non-dominant solutions and con-verge to optimal solutions quickly.
Key words:    algorithms    artificial intelligence    computer simulation    convergence of numerical methods    decision making    iterative methods    mapping    multiobjective optimization    probability    sampling    three dimensional    unmanned aerial vehicles (UAV)    path planning    probability roadmap method    multi-objective ant colony algorithm   
收稿日期: 2013-10-28     修回日期:
DOI:
基金项目: 国家自然科学基金(61374032);陕西省自然科学基金(2013JQ8026)资助
通讯作者:     Email:
作者简介: 刘洋(1988-),西北工业大学博士研究生,主要从事路径规划及智能算法的研究。
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