无人机雁行仿生群飞路径规划
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摘要
为解决单架无人机因互相之间没有通信机制而无法独立进行路径规划的问题,提出一种仿生雁群路径航路选择的无人机群飞路径规划。介绍算法原理,将无人机初始化为粒子后,在无人机群中确定主机、僚机。依据遗传算法基础原理,将仿生学引入到无人机群协同编队飞行航点规划当中,使用遗传算法对组群飞行的主机航路进行路径规划,产生需要的解或最优解;通过模仿雁群跟随的策略,设计僚机跟随主机的算法,从而实现组群飞行,并进行了实验验证。实验结果表明,该研究对无人机群飞行控制有一定的参考价值。
In order to solve the problem that single UAV cannot plan route independently since there is no communication mechanism between each other, an UAV route planning of bionic goose group path selection is proposed.Introduce the algorithm principle. After the UAV is initialized into particles, the host and the wing aircraft are identified in the UAV group. According to the basic principle of genetic algorithm, bionics is introduced into the planning of UAV group cooperative flying point plane. The genetic algorithm is used to plan the path of the host flight path of group flying, and the solution or optimal solution is generated. By simulating the strategy followed by the geese group, the algorithm of the downtime following the host was designed to realize the group flight. The flight test was carried out. The experimental results show that the research has certain reference value for UAV group flight control.
In order to solve the problem that single UAV cannot plan route independently since there is no communication mechanism between each other, an UAV route planning of bionic goose group path selection is proposed.Introduce the algorithm principle. After the UAV is initialized into particles, the host and the wing aircraft are identified in the UAV group. According to the basic principle of genetic algorithm, bionics is introduced into the planning of UAV group cooperative flying point plane. The genetic algorithm is used to plan the path of the host flight path of group flying, and the solution or optimal solution is generated. By simulating the strategy followed by the geese group, the algorithm of the downtime following the host was designed to realize the group flight. The flight test was carried out. The experimental results show that the research has certain reference value for UAV group flight control.
引文
[1]程勇.无人机变后掠翼机构设计及仿真实验研究[D].北京:中国科学技术大学,2010.
[2]万婧.无人机自主编队飞行控制系统设计方法及应用研究[D].上海:复旦大学,2009.
[3]樊琼剑,杨忠,方挺,等.多架无人机协同编队飞行控制的研究现状[J].航空学报,2009,30(4):683-691.
[4]MENG L,XU R.Formation flight scheduling based on incomplete infromation[J].中国航空学报(英文版),2015,28(6):1747-1757.
[5]HORVATH J M.Ad-hoc secure communication networking based on formation flight technology:US,US8811265[P].2014.
[6]周静,向开恒.GPS技术的发展及在航天器导航定位编队飞行中的应用[J].航天器工程,2005(4):53-57.
[7]李相民,颜骥,刘波.多无人机编队自主协同控制架构[J].电光与控制,2015,22(3):1-6.
[2]万婧.无人机自主编队飞行控制系统设计方法及应用研究[D].上海:复旦大学,2009.
[3]樊琼剑,杨忠,方挺,等.多架无人机协同编队飞行控制的研究现状[J].航空学报,2009,30(4):683-691.
[4]MENG L,XU R.Formation flight scheduling based on incomplete infromation[J].中国航空学报(英文版),2015,28(6):1747-1757.
[5]HORVATH J M.Ad-hoc secure communication networking based on formation flight technology:US,US8811265[P].2014.
[6]周静,向开恒.GPS技术的发展及在航天器导航定位编队飞行中的应用[J].航天器工程,2005(4):53-57.
[7]李相民,颜骥,刘波.多无人机编队自主协同控制架构[J].电光与控制,2015,22(3):1-6.