改进RRT算法的四旋翼无人机路径规划方法
An Optimizing RRT Algorithm for Quadrotor UAV Path Planning
冯迎宾 1赵子君 1晏佳华1
作者信息
- 1. 沈阳理工大学 自动化与电气工程学院,沈阳 110159
- 折叠
摘要
针对快速扩展随机树(rapidly-exploring random tree,RRT)算法在无人机路径规划过程中采样次数多、生成路径曲折等问题,提出了一种将路径重规划策略和平滑度优化相结合的路径规划算法.首先,通过重新构造采样区域降低RRT算法采样次数,利用目标偏向寻优策略为RRT算法添加导向性;其次,在筛选初始航迹点的同时引入无人机性能约束;然后,利用B样条对重规划路径进行平滑处理;最后,利用Matlab对所提出的算法进行仿真实验.实验结果为平均采样次数为386 次,平均运行时间为0.43 s,平均航迹距离为1 392.16(无量纲),表明了算法可有效降低采样次数并改善路径平滑性.
Abstract
For the case of multiple sampling and tortuous path generated by RRT in the process of UAV path planning,an algorithm combined with path re-planning strategy and smoothness optimi-zation is proposed.First,sampling area is restructured to reduce the sampling frequency of RRT al-gorithm,and the goal towards optimization strategy is used to guide RRT algorithm.Second,UAV performance constraint is introduced while filtering initial track points.Then,B-spline is used to smooth the re-planning path.Finally,the proposed algorithm is simulated by Matlab.Experimental results show that the average number of sampling is 386,the average running time is 0.43 seconds,and the average track distance is 1 392.16(dimensionless).It is concluded that the algorithm can effectively reduce the number of sampling and improve path smoothness.
关键词
四旋翼无人机/快速扩展随机树/航迹平滑/B样条曲线Key words
quadrotor UAV/rapidly-exploring random tree/track smoothing/path smooth/B-spline curve引用本文复制引用
基金项目
辽宁省教育厅高等学校基本科研项目(LJKMZ20220614)
出版年
2024
NETL
NSTL
万方数据