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基于改进蚁狮算法的无人机三维航迹规划

黄长强 赵克新

黄长强, 赵克新. 基于改进蚁狮算法的无人机三维航迹规划[J]. 电子与信息学报, 2018, 40(7): 1532-1538. doi: 10.11999/JEIT170961
引用本文: 黄长强, 赵克新. 基于改进蚁狮算法的无人机三维航迹规划[J]. 电子与信息学报, 2018, 40(7): 1532-1538. doi: 10.11999/JEIT170961
HUANG Changqiang, ZHAO Kexin. Three Dimensional Path Planning of UAV with Improved Ant Lion Optimizer[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1532-1538. doi: 10.11999/JEIT170961
Citation: HUANG Changqiang, ZHAO Kexin. Three Dimensional Path Planning of UAV with Improved Ant Lion Optimizer[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1532-1538. doi: 10.11999/JEIT170961

基于改进蚁狮算法的无人机三维航迹规划

doi: 10.11999/JEIT170961
基金项目: 

国家自然科学基金(61601505),航空科学基金(20155196022)

详细信息
    作者简介:

    黄长强: 男,1961年生,教授,博士生导师,研究方向为无人机总体设计与技术. 赵克新: 男,1992年生,硕士生,研究方向为无人机武器系统设计.

  • 中图分类号: V279

Three Dimensional Path Planning of UAV with Improved Ant Lion Optimizer

Funds: 

The National Natural Science Foundation of China (61601505), The Aviation Science Foundation (20155196022)

  • 摘要: 无人机3维航迹规划是任务规划中最复杂、重要的部分,针对基本蚁狮算法在解决3维航迹规划时能力不足的问题,首先在蚂蚁的行为中引入混沌调节因子,在蚁狮的行为中引入反调节因子,提高了算法的探索能力和开发能力;其次在建立3维环境模型的基础上,充分利用地形和约束信息,缩减搜索空间;最后将改进后的算法应用于3维航迹规划,并与原算法进行对比, 实现在线局部重规划。仿真实验结果验证了改进方法的可行性和优越性。
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出版历程
  • 收稿日期:  2017-10-19
  • 修回日期:  2018-03-21
  • 刊出日期:  2018-07-19

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