%0 Journal Article
%T Application of normal cloud based adaptive genetic algorithm inUAV path planning<br>基于正态云自适应遗传算法的无人机航路规划
%A CHENG Xiao-dong
%A ZHOU De-yun
%A HE Peng
%A ZHANG Kun
%A <br>成晓东
%A 周德云
%A 何　鹏
%A 张　堃
%J 计算机应用研究
%D 2012
%I 
%X Sequential genetic algorithm SGA easily gets stuck at a local optimum and has a slow convergent speed. To overcome its shortage, this paper presented NCAGA for UAV path planning. It applied a novel method of encoding based on rectangular plane coordinate system, which simplified the complexity of encoding and achieved a higher planning speed. The improved genetic algorithm combined with the normal X-condition cloud generator to adjust the probability of crossover and mutation adaptively. The stable tendency of normal cloud contributed a higher convergence speed and character of randomness conduced to a lower possibility of premature. Simulation results demonstrate that NCAGA is able to plan path quickly that made UAV avoid the dangerous areas with a higher effectiveness and success rate, so that it has a wide application prospect.
%K unmanned aerial vehicle（UAV）
%K normal cloud model
%K genetic algorithm
%K path planning
%K adaptation<br>无人机
%K 正态云模型
%K 遗传算法
%K 航路规划
%K 自适应
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=8D8174D12B4331BFCF25DA2B5C650BD4&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=59906B3B2830C2C5&sid=9783B4CE663233DC&eid=27F7B07D2C5FAE8C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=15