ATD-DBO驱动的无人机在不规则区域的渗透路径规划
Penetration Path Planning of UAV Driven by ATD-DBO in Irregular Areas
袁晓飞 1白梅娟 1王智慧 2尹茂振 2侯帅 1周敏敏1
作者信息
- 1. 河北工程大学信息与电气工程学院,河北邯郸 056038
- 2. 远光能源互联网产业发展(横琴)有限公司,北京 100176
- 折叠
摘要
城市无人机渗透作战中使用智能无人机执行隐蔽穿插、渗入和目标定位等任务,但其面临着城市环境复杂、空域限制等挑战.为了解决城市渗透背景下无人机的路径规划难题,提出了一种ATD-DBO(Adaptive T Distribution-Dung Beetle Optimizer)驱动的无人机在不规则区域的渗透路径规划算法.首先,提出融合城市建筑物分布、岗哨位置以及无人机特性的无人机城市渗透模型.其次,提出了虫口混沌映射初始化种群、自适应t分布和动态变异策略扰动蜣螂位置和将非精英个体进行二次变异的ATD-DBO算法.最后,提出了一种融合城市实战不规则区域场景和打击意图的快速突进模型.实验证明,算法规划出的路径在有效避开岗哨位置的同时能够确保路径较短.
Abstract
In the penetration operation of urban UAVs,intelligent UAVs are used for covert interpenetration,penetration and target positioning,but they are faced with challenges such as complex urban environment and airspace restrictions.In order to solve the path planning problem of UAV under the background of urban penetration,an ATD-DBO (Adaptive T Distribution-Dung Beetle Optimizer) driven penetration path planning algorithm for UAV in irregular areas is proposed. Firstly,a UAV urban penetration model integrating urban building distribution,sentry position and UAV characteristics is proposed. Secondly,an ATD-DBO algorithm is proposed to initialize the population by the chaotic map of the insect population,the adaptive t distribution and the dynamic mutation strategy to disturb the position of the dung beetle and the secondary mutation of the non-elite individuals. Finally,a fast advance model integrating urban actual irregular area scene and attack intention is proposed. Experiments show that the path planned by the algorithm can effectively avoid the sentry position and ensure that the path is short.
关键词
城市渗透模型/不规则突进区域/蜣螂优化算法/优选策略Key words
urban penetration model/irregular penetration area/dung beetle optimization algorithm/optimal selection strategy引用本文复制引用
基金项目
河北省自然科学基金面上项目(F2021402009)
河北省自然科学基金面上项目(A2020402013)
出版年
2024
NETL
NSTL
万方数据