Adapting Swarm Intelligence to a Fixed Wing Unmanned Combat Aerial Vehicle Platform
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Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The majority of the swarm UAV studies focus on a single aspect, only investigating the stages such as formation development, path planning, or target tracking for a swarm currently in mission flight. Besides, the dynamic coordination and operation of the system based on the new commands that can be transmitted to the swarm during the mission are not taken into account; that is, the input of the ground resources is often ignored. In this study, all stages of a swarm of unmanned combat aerial vehicles (UCAV), from take-off to the end of the mission, are detailed in a single holistic framework, including communication with the ground station and intercommunication between swarm members. The designed solution is a platform that will enable the swarm structure to prevail by developing alternative strategies and tactics against existing manned or unmanned air, land, and sea platforms. In this context, operational algorithms have been developed for fixed-wing, fully autonomous controlled UCAVs, which can successfully detect in-sight and beyond-sight targets for a desired period of time, and can communicate seamlessly with ground stations. Furthermore, dynamic swarm-type algorithms have been developed in order to fulfill the desired task in the event of the loss of any UCAV during the mission, to replace the lost vehicle with a new vehicle, and to communicate directly with the UCAVs in the swarm. As a result of adapting swarm intelligence to the UCAV platform, all individuals in the swarm perform tasks such as taking off in formation, adding or removing new individuals to the swarm, and formation protection. Moreover, they have the ability to change direction in a swarm, change formation, split or merge, navigate, ascend and descend, and simultaneous/sequential auto-landing as a swarm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Açıklama
Anahtar Kelimeler
Flight formation, Operational algorithms, Swarm systems, Target detection, Tracking, UAV
Kaynak
Studies in Big Data
WoS Q Değeri
Scopus Q Değeri
Q3
Cilt
132
