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http://dx.doi.org/10.12673/jant.2020.24.5.382

Optimal Surveillance Trajectory Planning for Illegal UAV Detection for Group UAV using Particle Swarm Optimization  

Lim, WonHo (Department of Aviation Industry and System Engineering, Inha University)
Jeong, HyoungChan (Department of Aviation Industry and System Engineering, Inha University)
Hu, Teng (Department of Electronic Engineering, Inha University)
Alamgir, Alamgir (Department of Electronic Engineering, Inha University)
Chang, KyungHi (Department of Electronic Engineering, Inha University)
Publication Information
Journal of Advanced Navigation Technology / v.24, no.5, 2020 , pp. 382-392 More about this Journal
Abstract
The use of unmanned aerial vehicle (UAV) have been regarded as a promising technique in both military and civilian applications. Nevertheless, due to the lack of relevant and regulations and laws, the misuse of illegal drones poses a serious threat to social security. In this paper, aiming at deriving the three-dimension optimal surveillance trajectories for group monitoring drones, we develop a group trajectory planner based on the particle swarm optimization and updating mechanism. Together, to evaluate the trajectories generated by proposed trajectory planner, we propose a group-objectives fitness function in accordance with energy consumption, flight risk. The simulation results validate that the group trajectories generated by proposed trajectory planner can preferentially visit important areas while obtaining low energy consumption and minimum flying risk value in various practical situations.
Keywords
3D path planning; Particle swarm optimization; Group unmanned aerial vehicles; Group trajectory planner;
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