In recent years, unmanned aerial vehicles have been used in all areas of our lives. The prevalence of UAVs is gradually increasing compared to manned platforms in terms of ease of use and the advantages they bring on task type diversity. Unmanned platforms in every field, from space systems to terrestrial and marine systems, are becoming widespread in terms of cost-effectiveness and not risking human life.

    The swarm UAV concept is used in commercial areas such as petroleum and pipeline checking applications (Hausamann et al., Aircraft Eng Aerospace Technol 77(5):352–360. https://doi.org/10.1118/00022660510617077, 2005; Katrasnik et al., IEEE Trans Power Deliv 25(1):485–493. https://doi.org/10.1109/TPWRD.2009.2035427, 2010), cargo applications (Palunko et al., Robot Autom Magaz 19(3):69–79. https://doi.org/10.1109/MRA.2012.2205617, 2012), and the movie sector (Galvane, Automated cinematography with unmanned aerial vehicles. In: Eurographics workshop on intelligent cinematography and editing, pp 23–30. https://doi.org/10.2312/wiced.20161097, 2016). In addition, the use of UAVs in light shows and show areas has increased recently. The development of new relative navigation methods of UAV has a financial aspect. Because of these factors, some academic studies are focused on UAV formation subjects. In addition to the civilian use of UAVs, the diversity of military usage areas and parallel to the development in unmanned aerial vehicle technology has brought the necessity of transition from single UAV use to multiple UAVs. Unmanned aerial vehicles (UAVs) contribute to the development of military power due to their success in missions such as surveillance, reconnaissance, attack, and defense, as well as economic and political power. In addition, due to low development costs compared to manned aircraft, unlimited manoeuvrability, and low risk of loss of life, private sector UAV applications, including manned reconnaissance, weather, forestry, agriculture, and photogrammetry, perform civil and military tasks beyond the capabilities of a manned aircraft (Dongwoo et al., Aerosp Sci Technol 76:412–420. https://doi.org/10.1016/j.ast.2018.01.026, 2018). However, a single UAV can only operate in a limited area and is ineffective compared to multiple drones on a mission. Swarm with the approach and multitasking can be performed. The swarm UAV operation does not require any change in the limits and performance of each drone, as well as allowing them to perform an assigned task through collaboration between all or part of the UAVs that make up the swarm to take advantage of the accuracy and efficiency allowed by diversity in the swarm approach (Dongwoo et al., Aerosp Sci Technol 76:412–420. https://doi.org/10.1016/j.ast.2018.01.026, 2018). In addition to this, many researchers are interested in flying UAV platforms in cluster architecture in near or distant formation geometries and performing their tasks.

    Relative navigation is used in different platforms for rendezvous, formation flight, and stereo imaging, which aims with UAVs and terrestrial or naval autonomous vehicles (Murtazin and Budylov, Acta Astron 67:900–909. https://doi.org/10.1016/j.actaastro.2010.05.012, 2010; Ma et al., Acta Astron 81:335–347. https://doi.org/10.1016/j.actaastro.2012.08.003, 2012). In this study, UAV formation flight methods are focused on and compared. In the UAV formation architecture, criteria such as method, sensor selection, and the effect of the mission on the flight path and formation geometry effect. Relative navigation is looking for the most optimal state estimates about the position and velocity of one platform relative to the other one (Alonso et al., Vision-based relative navigation for formation flying of spacecraft. In: AIAA-2000, p 4439. https://doi.org/10.2514/6.2000-4439, 2010).

    There are navigation and relative navigation methods that are traditional as GNSS & INS integrated or ground-based methods. However, within these methods, the platform that makes up the flock requires extra connectivity between the platform components and the sensor fusion subsystems (Erkec and Hajiyev, Traditional methods on relative navigation of small satellites, 2019. In: 9th international recent advances in space technologies conference (RAST), Istanbul, pp 869–874. https://doi.org/10.2514/RAST.2019.8767777, 2019). In addition, the other method approach is visual sensor-based fully autonomous freedom of movement using optical and image processing sensors and sensing and tracking models in parallel with the developing image processing and computing technologies (parallel programming, high-capacity processors) and is visual sensor-based methods independent of external systems. The new relative navigation models aim to avoid complexity and incremental errors.

    The main highlights of the paper can be summarized as follows. The main focussing subject of this study is the Guidance, Navigation, Control (GNC) architecture of UAV’s formation. Control approach requirements are denoted. Second, target UAV’s state vector tracking, estimation, and control models are explained. Collision avoidance can be executed by the relative state vector estimation and control signals during formation. Algorithms used for relative state vector estimations of UAVs within the formation are highlighted. Third, the comparisons of relative models are defined with different aspects within one hand (Erkec and Hajiyev, Int J Aviation Sci Technol 1(2):52–65. https://doi.org/10.23890/IJAST.vm01is02.0202, 2020).

    This study is about the relative navigation systems of UAVs within formation/cluster flight. First, the concepts and methods in cluster UAV technology and architecture are explained. The relative navigation model comparison of UAVs is based on other systems (Inertial Navigation Systems (INS) and Global Navigation Satellite Systems (GNSS)). Sensors placed in UAV platforms are used separately or integrated to solve relative navigation problems. Their areas of use differ according to the platform type and environment. This study aims to estimate the algorithms of UAVs during flight and the effects of relative navigation systems.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Swarm Architecture of UAVs


    Weitere Titelangaben:

    Sustainable aviat.


    Beteiligte:
    Karakoc, T. Hikmet (Herausgeber:in) / Colpan, Can Ozgur (Herausgeber:in) / Dalkiran, Alper (Herausgeber:in) / Erkec, Tuncay Yunus (Autor:in) / Hajiyev, Chingiz (Autor:in)


    Erscheinungsdatum :

    2022-11-26


    Format / Umfang :

    22 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Obstacle Avoidance Manager for UAVs Swarm*

    Madridano, Angel / Al-Kaff, Abdulla / Flores, Pablo et al. | IEEE | 2020


    Coordinated search with a swarm of UAVs

    Waharte, S. / Trigoni, N. / Julier, S. | Tema Archiv | 2009


    Multi-Path Planning Method for UAVs Swarm Purposes

    Madridano, Angel / Al-Kaff, Abdulla / Gomez, David Martin et al. | IEEE | 2019