无线电通信技术2024，Vol.50Issue(4)：713-719,7.DOI:10.3969/j.issn.1003-3114.2024.04.013
高密度场景下基于改进A*算法的无人机路径规划
Unmanned Aerial Vehicle Path Planning Based on Improved A*Algorithm in High-density Scenarios
赵烈海 1李大鹏1
作者信息
- 1. 南京邮电大学通信与信息工程学院,江苏南京 210003
- 折叠
摘要
Abstract
In response to the challenge of achieving real-time path planning for unmanned aerial vehicles flying in High-density ur-ban environments with numerous obstacles,this paper introduces a novel algorithm known as Jump A*(JA*).Building upon A*algo-rithm and incorporating Jump Point Search(JPS)strategy,JA* algorithm is proposed.Initially,we extend A* algorithm into three di-mensions and introduce a three-dimensional diagonal distance measurement that precisely represents actual path cost,thereby reducing search time.Subsequently,building upon the two-dimensional Jump Point Search strategy,we extend it to three dimensions,resulting in a 3D-JPS strategy.This 3D-JPS strategy replaces the geometric neighbor expansion used in A* algorithm and significantly reduces the number of expanded nodes.We conducted path planning simulations on complex three-dimensional grid maps with obstacle densities ranging from 0.1 to 0.4.Simulation results indicate that,in comparison to A* algorithm,JA* algorithm exhibits almost iden-tical path lengths while significantly reducing the number of evaluated nodes.This substantial reduction in node expansion leads to a notable improvement in search speed,particularly in near-ground urban environments characterized by High-density obstacles.关键词
路径规划/跳点搜索/A*算法/三维栅格地图/高密度障碍物Key words
path planning/JPS/A* algorithm/3D grid map/high-density obstacles分类
信息技术与安全科学引用本文复制引用
赵烈海,李大鹏..高密度场景下基于改进A*算法的无人机路径规划[J].无线电通信技术,2024,50(4):713-719,7.
