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
收藏
页码:8363 / 8370
页数:7
相关论文
共 17 条
[11]  
Cobano, Jose A., Et al., Data retrieving from heterogeneous wireless sensor network nodes using UAVs, Journal of Intelligent & Robotic Systems, 60, 1, pp. 133-151, (2010)
[12]  
Yanmaz E., Kuschnig R., Quaritsch M., Et al., On path planning strategies for networked unmanned aerial vehicles, 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 212-216, (2011)
[13]  
Ozalp N., Sahingoz O.K., Optimal UAV path planning in a 3D threat environment by using parallel evolutionary algorithms, IEEE 2013 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 308-317, (2013)
[14]  
Heng, Lionel, Et al., Autonomous obstacle avoidance and maneuvering on a vision-guided MAV using on-board processing, IEEE International Conference on Robotics and Automation, (2011)
[15]  
Ergezer, Et al., Path planning for multiple unmanned aerial vehicles, Signal Processing and Communications Applications Conference, (2012)
[16]  
Ergezer, Halit, Leblebiciolu K., 3D Path Planning for Multiple UAVs for Maximum Information Collection, Journal of Intelligent & Robotic Systems, 73, 1-4, pp. 737-762, (2014)
[17]  
Siek J.G., Lee L.-Q., Lumsdaine A., The Boost Graph Library User Guide and Reference Manual, (2002)