计算机应用研究2024，Vol.41Issue(10)：3015-3020,6.DOI:10.19734/j.issn.1001-3695.2024.01.0028
基于TSACO及动态避障策略的无人机路径规划
UAV path planning based on TSACO and dynamic obstacle avoidance strategy
江南 1徐海芹 1邢浩翔1
作者信息
- 1. 东华大学信息科学与技术学院,上海 201620
- 折叠
摘要
Abstract
This paper proposed an improved ant colony optimization named TSACO and an enhanced velocity obstacle(VO)to solve the UAV path planning problem.The TSACO incorporated non-uniform initial pheromone distribution,a turning heuristic function,and an elite ant system to improve the convergence speed and reduce the number of path corners during global plan-ning.The enhanced VO integrated the UAV's dynamic equation,adaptive collision radius and emergency collision cone,along with an optimal velocity selection approach to increase real-time and safe local obstacle avoidance during local planning.Simu-lation experiments demonstrate that the proposed algorithms have better effectiveness in terms of path length,number of turns,and dynamic obstacle avoidance compared to other algorithms.关键词
无人机/路径规划/蚁群算法/速度障碍法Key words
unmanned aerial vehicle(UAV)/path planning/ant colony optimization/velocity obstacle分类
航空航天引用本文复制引用
江南,徐海芹,邢浩翔..基于TSACO及动态避障策略的无人机路径规划[J].计算机应用研究,2024,41(10):3015-3020,6.
