UAV Path Planning Based on an Improved Ant Colony Algorithm

被引：12

作者：

Huan, Liu ^{[1
]}

Ning, Zhang ^{[2
]}

Qiang, Li ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Informat & Commun, Wuhan, Hubei, Peoples R China

[2] 95402 Army, Guiyang, Guizhou, Peoples R China

来源：

2021 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT AUTONOMOUS SYSTEMS (ICOIAS 2021) | 2021年

关键词：

UAV; path planning; ant colony algorithm; simulation;

D O I：

10.1109/ICoIAS53694.2021.00070

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve operational efficiency and survival probability, the optimal path of an UAV should be designed before the UAV performs a mission. The basic ant colony algorithm is easy to fall into the local optimum, and slow convergence speed. This paper improves the basic algorithm from two aspects: guidance factor and node pheromone update. The improved algorithm proposed in this paper can overcome the problems of the basic ant colony algorithm. The simulation results show that the improved ant colony algorithm is feasible for UAV path planning and the flight path optimization ability of UAV is improved.

引用

页码：357 / 360

页数：4