基于定向探索树算法的四旋翼无人机路径规划  

Quadrotor UAV Path Planning Based on Rapidly-exploration Directional Tree Algorithm

作　　者：胡世军[1] 刘海亮 王兵雷 苏文科 Hu Shijun;Liu Hailiang;Wang Binglei;Su Wenke(School of Mechanical and Electrical Engineering,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区：[1]兰州理工大学机电工程学院,甘肃兰州730050

出　　处：《系统仿真学报》2025年第2期311-324,共14页Journal of System Simulation

基　　金：国家自然科学基金(51465034)。

摘　　要：针对四旋翼无人机在复杂环境中进行路径规划时,RRT存在规划成功率低、收敛速度慢、路径次优等问题,提出一种定向探索树算法。使用定向采样策略,以提高树扩展的方向性,通过引入自适应目标调整策略和枝条扩展策略,使树能够快速向目标点扩展的同时又能够避开障碍物。通过剪枝处理去除初始路径中的允余点,再对剪枝处理后的路径进行航迹修正和平滑处理,得到最优航线。仿真结果表明:所提算法在所有的测试中都是成功的。与传统RRT和改进RRT算法相比,在多障碍物环境中,规划时间缩短了91.9%和67%,路径长度缩短了37%和6%;在狭窄环境中,规划时间缩短了88.3%和70%,路径长度缩短了36%和5.6%。Aiming at the problems of low planning success rate,slow convergence speed,and suboptimal paths in the RRT algorithm for quadrotor UAV path planning of in complex environments,a directional exploration tree algorithm is proposed,which uses a directional sampling strategy to improve the directionality of the tree expansion,and by introducing an adaptive target adjustment strategy and a branch expansion strategy,the tree can expand quickly towards the target point while avoiding obstacles.The redundant points in the initial path are removed by the pruning process,and then the trajectory correction and smoothing process are performed on the pruned path to obtain the optimal route.Simulation results show that the proposed algorithm is successful in all tests.relative to the traditional RRT and improved RRT algorithms in multi-obstacle environments,in multi-obstacle environments,in terms of planning time,the proposed algorithm reduces 91.9%and 67%,in terms of path length,the proposed algorithm reduces 37%and 6%;in narrow environments compared in terms of planning time,the proposed algorithm reduces 88.3%and 70%,in terms of path length,the proposed algorithm reduces 36%and5.6%.

关 键 词：定向采样 自适应目标 剪枝优化 平滑处理 四旋翼无人机 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]