[1]闫怡汝,王寅.基于鸽群优化的复杂环境下无人机侦查航迹优化 [J].郑州大学学报(工学版),2019,40(04):3.[doi:10.13705/j.issn.1671-6833.2019.04.016]
　Yan Yiru,Wang Yin. undefined Pigeon-inspired Optimization Based Trajectory Planning Methodfor UAVs in a Complex Urban Environment [J].Journal of Zhengzhou University (Engineering Science),2019,40(04):3.[doi:10.13705/j.issn.1671-6833.2019.04.016]
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基于鸽群优化的复杂环境下无人机侦查航迹优化
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
40
期数:
2019年04期
页码:
3
栏目:
出版日期:
2019-07-10

文章信息/Info

Title:
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Pigeon-inspired Optimization Based Trajectory Planning Methodfor UAVs in a Complex Urban Environment
作者:
闫怡汝; 王寅
南京航空航天大学航天学院
Author(s):
Yan Yiru；Wang Yin
School of Astronautics, Nanjing University of Aeronautics and Astronautics
关键词:
鸽群优化; 无人机; 动态规划; 航路规划
Keywords:
Pigeon flock optimization; UAV; dynamic programming; route planning
DOI:
10.13705/j.issn.1671-6833.2019.04.016
文献标志码:
A
摘要:
地表环境的复杂性以及机载探测装置探测范围的约束,使得无人机在某些方位无法实现对地面目标的有效监测因此,在设计无人机侦查航路时需要综合考虑无人机飞行性能与目标可视范围等条件针对这一问题,提出了一种基于改进鸽群优化与动态规划算法的无人机侦查航路优化方法.首先,通过分析机载探测蓑置视场与地表环境的相对空间关系,得到了目标周围空域的可视范围随后,结合鸽群优化理论柜架与动态规范方法对无人机的最优侦查航迹进行求解为提高鸽群优化算法在求解目标排序问題中的效率,提出了一种离散化的鸽群优化改进机制仿真结果表明,侦查航迹优化算法在捉高任务完成度的同时具有很高的求解效率和准确性
Abstract:
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In this paper, a trajectory planning approach based on the principle of dynamie programming andframe work of pigeon inspired optimization( PIO) was proposed for UAV surveillance tasks. In this approachthe sensor visibility was firstly analyzed by considering the occ lusions caused by terrain feature, and the delee.table areas of the targets were approximated by a series of poly gons. To determine the optimal trackable path togons were replaced by with their centers firstly, which allowed tocover all target sites, the target visibility poly obtained an initial solution by optimizing the order of the targets to be visited. In the following step of the algorithm, a path refinement scheme combing dynamic programming and PIO was proposed to refine the initialconsidering t he sensor visibility and turning radius constraint of the UAV. Comparative simulationroute

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更新日期/Last Update: 2019-07-29