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Cited by 916

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.

Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review

Open access
Mohsan, Syed Agha Hassnain, Khan, Muhammad Asghar, Noor, Fazal, Ullah, Insaf, Alsharif, Mohammed H.·2022·Drones
DOI 10.3390/drones6060147
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Abstract

Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs.

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Citations

Cites

Research works printed but not linked: 39

  1. Kim, 2018, CBDN: Cloud-Based Drone Navigation for Efficient Battery Charging in Drone Networks, IEEE Trans. Intell. Transp. Syst., 20, 4174, 10.1109/TITS.2018.2883058 · doi:10.1109/tits.2018.2883058
  2. Khan, M.A., Alvi, B.A., Safi, A., and Khan, I.U. (2018, January 28–29). Drones for Good in Smart Cities: A Review. Proceedings of the International Conference on Electrical, Electronics, Computers, Communication, Mechanical and Computing (EECCMC), Tamil Nadu, India.
  3. Zhang, 2016, Optimizing Itinerary Selection and Charging Association for Mobile Chargers, IEEE Trans. Mob. Comput., 16, 2833, 10.1109/TMC.2016.2641446 · doi:10.1109/tmc.2016.2641446
  4. Raciti, A., Rizzo, S.A., and Susinni, G. (2018, January 7–10). Drone charging stations over the buildings based on a wireless power transfer system. Proceedings of the 2018 IEEE/IAS 54th Industrial and Commercial Power Systems Technical Conference (I & CPS), Niagara Falls, ON, Canada. · doi:10.1109/icps.2018.8369967
  5. Rohan, A., Rabah, M., Talha, M., and Kim, S.-H. (2018). Development of Intelligent Drone Battery Charging System Based on Wireless Power Transmission Using Hill Climbing Algorithm. Appl. Syst. Innov., 1. · doi:10.3390/asi1040044
  6. Pham, H., Smolka, S.A., Stoller, S.D., Phan, D., and Yang, J. (2015). A survey on unmanned aerial vehicle collision avoidance systems. arXiv.
  7. Ebeid, E., Skriver, M., and Jin, J. (September, January 30). A survey on open-source flight control platforms of unmanned aerial vehicle. Proceedings of the 2017 Euromicro Conference on Digital System Design (DSD), Vienna, Austria. · doi:10.1109/dsd.2017.30
  8. Ucgun, 2021, A review on applications of rotary-wing unmanned aerial vehicle charging stations, Int. J. Adv. Robot. Syst., 18, 17298814211015863, 10.1177/17298814211015863 · doi:10.1177/17298814211015863
  9. Zhao, X., Zhou, Z., and Zhu, X. (2018, January 5–8). Design of a lift-propulsion VTOL UAV system. Proceedings of the 2018 IEEE International Conference on Mechatronics and Automation (ICMA), Changchun, China. · doi:10.1109/icma.2018.8484448
  10. Zhang, Q., and Liu, H.H. (2019). Robust cooperative formation control of fixed-wing unmanned aerial vehicles. arXiv.
  11. Cai, G., Lum, K.-Y., Chen, B.M., and Lee, T.H. (2010, January 9–11). A brief overview on miniature fixed-wing unmanned aerial vehicles. Proceedings of the IEEE ICCA 2010, Xiamen, China. · doi:10.1109/icca.2010.5524453
  12. Dong, F., Li, L., Lu, Z., Pan, Q., and Zheng, W. (2019, January 20–24). Energy-efficiency for fixed-wing UAV-enabled data collection and forwarding. Proceedings of the 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China. · doi:10.1109/iccw.2019.8757098
  13. Gunarathna, J.K., and Munasinghe, R. (June, January 30). Development of a quad-rotor fixed-wing hybrid unmanned aerial vehicle. Proceedings of the 2018 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka. · doi:10.1109/mercon.2018.8421941
  14. Wen, 2018, Influence of wing tip vortex on drift of single rotor plant protection unmanned aerial vehicle, Nongye Jixie Xuebao/Trans. Chin. Soc. Agric. Mach., 49, 127
  15. De Souza BJ, O., and Endler, M. (2015, January 23–27). Coordinating movement within swarms of UAVs through mobile networks. Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), St. Louis, MO, USA.
  16. Pestana, J., Sanchez-Lopez, J.L., de la Puente, P., Carrio, A., and Campoy, P. (2014, January 27–30). A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition. Proceedings of the 2014 International Conference on Unmanned Aircraft Systems (ICUAS), Orlando, FL, USA. · doi:10.1109/icuas.2014.6842305
  17. Fotouhi, A., Ding, M., and Hassan, M. (2017, January 12–15). Understanding autonomous drone maneuverability for Internet of Things applications. Proceedings of the 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), Macau, China. · doi:10.1109/wowmom.2017.7974336
  18. Hempe, D. (2006, January 6–8). Unmanned aircraft systems in the United States. Proceedings of the US/Europe International Safety Conference, Washington, DC, USA.
  19. (2022, April 05). EASA UAS Workshop. Available online: https://www.easa.europa.eu/sites/default/files/dfu/ws_prod-g-doc-Events-2008-February-1-Overview-of-the-UAV-Industry-(UVS).pdf.
  20. Yinka-Banjo, C., and Ajayi, O. (2020). Sky-Farmers: Applications of unmanned aerial vehicles (UAV) in agriculture. Auton. Veh., 107–128. · doi:10.5772/intechopen.89488
  21. Decker, 2022, Economic policy choices and trade-offs for Unmanned aircraft systems Traffic Management (UTM): Insights from Europe and the United States, Transp. Res. Part A Policy Pract., 157, 40, 10.1016/j.tra.2022.01.006 · doi:10.1016/j.tra.2022.01.006
  22. Jawad, 2019, Wireless power transfer with magnetic resonator coupling and sleep/active strategy for a drone charging station in smart agriculture, IEEE Access, 7, 139839, 10.1109/ACCESS.2019.2943120 · doi:10.1109/access.2019.2943120
  23. Valente, 2011, An air-ground wireless sensor network for crop monitoring, Sensors, 11, 6088, 10.3390/s110606088 · doi:10.3390/s110606088
  24. Campi, T., Cruciani, S., and Feliziani, M. (2018). Wireless Power Transfer Technology Applied to an Autonomous Electric UAV with a Small Secondary Coil. Energies, 11. · doi:10.3390/en11020352
  25. Campi, T., Dionisi, F., Cruciani, S., De Santis, V., Feliziani, M., and Maradei, F. (2016, January 18–21). Magnetic field levels in drones equipped with wireless power transfer technology. Proceedings of the 2016 Asia-Pacific International Symposium on Electromagnetic Com-patibility (APEMC), Shenzhen, China. · doi:10.1109/apemc.2016.7522793
  26. Song, 2018, EMI reduction methods in wireless power transfer system for drone electrical charger using tightly coupled three-phase resonant magnetic field, IEEE Trans. Ind. Electron., 65, 6839, 10.1109/TIE.2018.2793275 · doi:10.1109/tie.2018.2793275
  27. Qin, 2021, Blockchain-enabled charging scheduling for unmanned vehicles in smart cities, J. Internet Technol., 22, 327
  28. Fazelpour, 2013, Considerable parameters of using PV cells for so-lar-powered aircrafts, Renew. Sustain. Energy Rev., 22, 81, 10.1016/j.rser.2013.01.016 · doi:10.1016/j.rser.2013.01.016
  29. Thipyopas, C., Sripawadkul, V., and Warin, N. (2019, January 3–6). Design and development of a small solar-powered UAV for environmental monitoring application. Proceedings of the 2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE), Yunlin, Taiwan. · doi:10.1109/ecice47484.2019.8942777
  30. Wu, 2018, Energy management strategy for solar-powered UAV long-endurance target tracking, IEEE Trans. Aerosp. Electron. Syst., 55, 1878, 10.1109/TAES.2018.2876738 · doi:10.1109/taes.2018.2876738
  31. Achtelik, M.C., Stumpf, J., Gurdan, D., and Doth, K.-M. (2011, January 25–30). Design of a flexible high performance quadcopter platform breaking the MAV endurance record with laser power beaming. Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA. · doi:10.1109/iros.2011.6048336
  32. Chen, 2015, Design and experiment for realization of laser wireless power transmission for small unmanned aerial vehicles, Int. Soc. Opt. Photonics, 9671, 96710N
  33. Lee, S., Lim, N., Choi, W., Lee, Y., Baek, J., and Park, J. (2020). Study on battery charging converter for MPPT control of laser wireless power transmission system. Electronics, 9. · doi:10.3390/electronics9101745
  34. Che, 2020, UAV-aided information and energy transmissions for cognitive and sustainable 5G networks, IEEE Trans. Wirel. Commun., 20, 1668, 10.1109/TWC.2020.3035425 · DOI
  35. Tiansawat, P., and Elliott, S. (2022, May 01). Unmanned Aerial Vehicles for Automated Forest Restoration. Available online: https://www.researchgate.net/profile/Stephen-Elliott-2/publication/350688583_Unmanned_Aerial_Vehicles_for_Automated_Forest_Restoration/links/614b3f56a3df59440ba46d20/Unmanned-Aerial-Vehicles-for-Automated-Forest-Restoration.pdf.
  36. Moura, M., de Oliveira, L., Sanquetta, C., Bastos, A., Mohan, M., and Corte, A. (2021). Towards amazon forest restoration: Automatic detection of species from UAV imagery. Remote Sens., 13. · doi:10.3390/rs13132627
  37. Jiang, B., Yang, J., and Song, H. (2020, January 6–9). Protecting Privacy from Aerial photography: State of the Art, Opportunities, and Challenges. Proceedings of the IEEE INFOCOM 2020—IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Toronto, ON, Canada. · doi:10.1109/infocomwkshps50562.2020.9162649
  38. Sands, T. (2021). Virtual Sensoring of motion using pontryagin’s treatment of hamiltonian systems. Sensors, 21. · doi:10.3390/s21134603
  39. Khan, M.A., Qureshi, I.M., Khan, I.U., Nasim, M.A., Javed, U., and Khan, M.W. (2018, January 25–27). On the performance of flying ad-hoc Network (FANET) with directional antennas. Proceedings of the 2018 5th International Multi-Topic ICT Conference (IMTIC), Jamshoro, Pakistan. · doi:10.1109/imtic.2018.8467274

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Metadata

Authors
Mohsan, S. A. H., Khan, M. A., Noor, F., Ullah, I., & Alsharif, M. H.
Venue
Drones
Publisher
MDPI AG
Published
2022-06-15
Volume
6
Issue
6
Pages
147
ISSN
2504-446X (ISSN-L)
DOI
10.3390/drones6060147
OpenAlex
W4282970004
Cited by
916
References
71
FWCI
80.95
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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