基于PH曲线的无人机路径规划算法  

Path Planning Based on PH Curves for Unmanned Aerial Vehicles

作　　者：王怿[1] 祝小平[1] 周洲[1] 

机构地区：[1]西北工业大学无人机特种技术重点实验室,陕西西安710072

出　　处：《计算机仿真》2013年第3期76-79,共4页Computer Simulation

摘　　要：研究了无人机可飞行路径规划问题,传统路径规划算法不能生成满足无人机运动学约束的可飞行路径。为解决上述问题,提出了将曲率连续的Pythagorean Hodograph(PH)曲线(又称勾股速端曲线)直接用于无人机路径规划的方法,利用PH曲线曲率连续、曲线平滑以及有理特性,在已知威胁的环境中可直接得到满足最大曲率约束且曲率连续的无人机可飞行路径。采用遗传模拟退火算法搜索避开环境中威胁体,并满足约束条件的最优PH路径,使仿真过程结合遗传算法和模拟退火算法的优点,取长补短,提高搜索效率,加强全局搜索能力。仿真结果表明,遗传模拟退火算法能在较少的进化代数下得到最优路径解,且所得的满足约束条件的PH路径曲率连续,为无人机飞行控制提供了依据。As the path produced by normal path planning algorithm cannot meet the constraint of UAVs＇ dynam- ics, the path planning algorithm that can produce flyable paths for UAVs was researched in this paper. In order to produce a flyable path, Pythagorean Hodograph （PH）curves which have continuous curvature were directly used in the proposed path planning algorithm. Taking the advantages of rational property, smaller elastic bending energy and con- tinuous curvature of PH curves, a path which has continuous curvature and meets the constraint of UAV＇ s maximum curvature can be directly produced to avoid the threats in the environment. The algorithm of genetic simulated annea- ling （GASA） was applied to search for the optimal PH path. This algorithm, which has the advantages of both genet- ic algorithm and simulated annealing, can improve the efficiency and the global search capacity of path planning. Simulation results show that the proposed algorithm can obtain the optimal solution in relatively fewer generations, and the obtained PH path which meets the constraints and has continuous curvature is easy for UAV to manoeuvre.

关 键 词：无人机 路径规划 勾股速端曲线 遗传算法 模拟退火算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]