Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm

Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the missi...

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Autores principales:	Wei Tan, Yong-jiang Hu, Yue-fei Zhao, Wen-guang Li, Xiao-meng Zhang, Yong-ke Li
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/747fe818c5624cdcb527d8ca7f00949d
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id	oai:doaj.org-article:747fe818c5624cdcb527d8ca7f00949d
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spelling	oai:doaj.org-article:747fe818c5624cdcb527d8ca7f00949d2021-11-22T01:11:37ZMission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm1530-867710.1155/2021/4154787https://doaj.org/article/747fe818c5624cdcb527d8ca7f00949d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4154787https://doaj.org/toc/1530-8677Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the mission planning of a single unmanned aerial vehicle. Based on that, we then investigate the multi-UAV cooperative system under the mission background of cooperative target destruction and show that it is a many-to-one rendezvous problem. A heterogeneous UAV cooperative mission planning model is then proposed where the mission background is generated based on the Voronoi diagram. We then adopt the tabu genetic algorithm (TGA) to obtain multi-UAV mission planning. The simulation results show that the single-UAV and multi-UAV mission planning can be effectively realized by the Voronoi diagram-TGA (V-TGA). It is also shown that the proposed algorithm improves the performance by 3% in comparison with the Voronoi diagram-particle swarm optimization (V-PSO) algorithm.Wei TanYong-jiang HuYue-fei ZhaoWen-guang LiXiao-meng ZhangYong-ke LiHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Wei Tan Yong-jiang Hu Yue-fei Zhao Wen-guang Li Xiao-meng Zhang Yong-ke Li Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
description	Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the mission planning of a single unmanned aerial vehicle. Based on that, we then investigate the multi-UAV cooperative system under the mission background of cooperative target destruction and show that it is a many-to-one rendezvous problem. A heterogeneous UAV cooperative mission planning model is then proposed where the mission background is generated based on the Voronoi diagram. We then adopt the tabu genetic algorithm (TGA) to obtain multi-UAV mission planning. The simulation results show that the single-UAV and multi-UAV mission planning can be effectively realized by the Voronoi diagram-TGA (V-TGA). It is also shown that the proposed algorithm improves the performance by 3% in comparison with the Voronoi diagram-particle swarm optimization (V-PSO) algorithm.
format	article
author	Wei Tan Yong-jiang Hu Yue-fei Zhao Wen-guang Li Xiao-meng Zhang Yong-ke Li
author_facet	Wei Tan Yong-jiang Hu Yue-fei Zhao Wen-guang Li Xiao-meng Zhang Yong-ke Li
author_sort	Wei Tan
title	Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
title_short	Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
title_full	Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
title_fullStr	Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
title_full_unstemmed	Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm
title_sort	mission planning for unmanned aerial vehicles based on voronoi diagram-tabu genetic algorithm
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/747fe818c5624cdcb527d8ca7f00949d
work_keys_str_mv	AT weitan missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm AT yongjianghu missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm AT yuefeizhao missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm AT wenguangli missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm AT xiaomengzhang missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm AT yongkeli missionplanningforunmannedaerialvehiclesbasedonvoronoidiagramtabugeneticalgorithm
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Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm

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