An algorithm of visual reconnaissance path planning for UAVs in complex spaces

被引：0

作者：

Shang, Bo ^{[1
]}

Wu, Chengdong ^{[1
]}

Hu, Yuchao ^{[1
]}

Yang, Jianyu ^{[1
]}

机构：

[1] College of Information Science and Engineering, Northeastern University, Shenyang

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 19期

关键词：

Complex space; Cost optimization; Path planning; UAV; Visual surveillance;

D O I：

10.12733/jcis11915

中图分类号：

学科分类号：

摘要：

UAVs have more and more applications on regional exploration, data collection and disaster relief because they are fast, flexible and unconstrained by terrains. This paper is focused on the strategy of visual reconnaissance by drones in complex spaces. The integer programming algorithm is used to minimize the number of pictures as well as ensuring the coverage. The number of shooting points in this paper decreases by 7.89% compared with that in Quaritsch's paper [7]. This article formulates the path planning problem as a Traveling Salesman Problem (TSP) in order to get the shortest flight path. The TSP model is solved by genetic algorithm and the path length decreases by 10.84% compared with that in Quaritsch's paper. Meanwhile, the uncovered area ratio only increases from 6.12% to 7.32%. Therefore, the cost decline is from 7% to 10%, and the monitoring quality is nearly the same when using the algorithm in this paper. 1553-9105/Copyright © 2014 Binary Information Press

引用

页码：8363 / 8370

页数：7

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