火力与指挥控制2024,Vol.49Issue(1) :111-117,123.DOI:10.3969/j.issn.1002-0640.2024.01.014

基于改进A*蚁群融合算法的路径规划研究

Research on Path Planning Based on Improved A* Ant Colony Fusion Algorithm

王锋 李凯璇 朱子文 朱磊 王海迪
火力与指挥控制2024,Vol.49Issue(1) :111-117,123.DOI:10.3969/j.issn.1002-0640.2024.01.014

基于改进A*蚁群融合算法的路径规划研究

Research on Path Planning Based on Improved A* Ant Colony Fusion Algorithm

王锋 1李凯璇 2朱子文 3朱磊 4王海迪3
扫码查看

作者信息

  • 1. 中北大学机电工程学院,太原 030051
  • 2. 中北大学智能武器研究院,太原 030051;西北工业集团有限公司,西安 710043
  • 3. 中北大学机电工程学院,太原 030051;中北大学智能武器研究院,太原 030051
  • 4. 北方自动控制技术研究所,太原 030006
  • 折叠

摘要

随着智能化技术的发展,无人车路径规划技术在未来无人战场上将发挥重要的作用.针对A*算法易发生碰撞障碍物的问题,提出通过改进转弯机制进行避碰.针对路径较长和不够平滑的问题,提出一种改进A*蚁群融合算法.仿真结果表明,使用改进A*蚁群融合算法得到的路径长度和平滑度更优,简单地图中路径长度减少2.34%,总转弯角度减小5.62%;复杂地图中路径长度减少2.62%,总转弯角度减小26.3%.因此,该算法在保证无人车避障的基础上,有利于其快速完成相应任务.

Abstract

With the development of intelligent technology,unmanned vehicle path planning technolo-gy will play an important role in the future unmanned battlefield.In response to the issue of A*algorithm being prone to collision with obstacles,an improved turning mechanism is proposed to avoid collisions.A modified A*ant colony fusion algorithm is proposed for path planning to address the issues of long and in-sufficiently smooth paths.The simulation results show that the obtained path length and smoothness are better with the improved A*ant colony fusion algorithm,with a 2.34%reduction in path length and a 5.62%reduction in total turning angle in simple maps.In complex maps,the length of the road path is re-duced by 2.62%,and the total turning angle is reduced by 26.3%.Therefore,this algorithm is beneficial for unmanned vehicles to quickly complete corresponding tasks while ensuring obstacle avoidance.

关键词

无人车/路径规划/A*蚁群融合算法/转弯机制

Key words

unmanned vehicles/path planning/A* ant colony fusion algorithm/turning mechanism

引用本文复制引用

出版年

2024
火力与指挥控制
火力与指挥控制研究会,火力与指挥控制专业情报网

火力与指挥控制

CSTPCD北大核心
影响因子:0.312
ISSN:1002-0640
参考文献量11
段落导航相关论文