Abstract
The use of GPS navigation systems for drone delivery in a dynamic environment has grown significantly in recent years. The potential of GPS navigation techniques in such a context for emergency purposes has not yet been fully explored. This paper presents a taxonomy for GPS-based navigation Unmanned Aerial Vehicles (UAVs) that identifies the major components of a navigation system for UAVs to deliver emergency medical aid. We demonstrate that these components are crucial and serve as a validation criterion when introducing a navigational routing algorithm into UAV delivery applications. The proposed taxonomy is a step toward developing a robust routing strategy that helps vendors and receivers understand and discuss the components of GPS navigation of UAVs for delivering emergency medical aid. We demonstrate the utility of the proposed taxonomy in the field of UAV/drone delivery utilizing GPS navigation. The proposed taxonomy facilitates an understanding of the classification groups, validation criteria, and future trends in drone applications aiming at reducing the time and cost of drone delivery systems.
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References
Sundar, K., Rathinam, S.: Algorithms for routing an unmanned aerial vehicle in the presence of refueling depots. IEEE Trans. Autom. Sci. Eng. 11(1), 287–294 (2014)
Song, B.D., Park, K., Kim, J.: Persistent UAV delivery logistics: MILP formulation and efficient heuristic. Comput. Ind. Eng. 120, 418–428 (2019)
Sanfridsson, J., et al.: Drone delivery of an automated external defibrillator – a mixed method simulation study of bystander experience. Scand. J. Trauma Resusc. Emerg. Med. 27(40), 1556–1561 (2019)
Zhang, G., Hsu, L.T.: A new path planning algorithm using a GNSS localization error map for UAVs in an urban area. J. Intell. Rob. Syst. 94(2), 219–235 (2019)
Cordeau, J.F., Laporte, G., Mercier, A.: A unified tabu search heuristic for vehicle routing problems with time windows. J. Oper. Res. Soc. 52(8), 928–936 (2001)
Caffrey, S.L., Willoughby, P.J., Pepe, P.E., Becker, L.B.: Public use of automated external defibrillators. N. Engl. J. Med. 347(1242), 1–7 (2002)
Sanchez, J.L., Wang, M., Olivares, M.A., Molina, M., Voos, H.: A real time 3D path planning solution for Collision free navigation of multirotor aerial robots in dynamic environments. J. Intell. Robot. Syst. 93, 33–53 (2019)
Sampedro, C., Rodriguez, A.R., Bavle, H., Carrio, A., Puente, P., Campoy, P.: A fully-autonomous aerial robot for search and rescue applications in indoor environments using learning-based techniques. J. Intell. Rob. Syst. 29, 601–627 (2019)
Yuan, H., et al.: Target detection, positioning and tracking using new UAV gas sensor systems: simulation and analysis. J. Intell. Rob. Syst. 94, 871–882 (2019)
Fakhrulddin, S.S., Gharghan, S.K., Naji, A.A., Chahl, J.: An advanced first aid system based on an unmanned aerial vehicles and a wireless body area sensor network for elderly persons in outdoor environments. Sensors 19(13), 1–28 (2019)
Kim, S.J., Lim, G.J., Cho, J., Cote, M.J.: Drone-aided healthcare services for patients with chronic diseases in rural areas. J. Intell. Robot. Syst. 88(13), 163–180 (2017)
Aswini, N., Krishna, E.K., Uma, S.V.: UAV and obstacle sensing techniques – a perspective. Int. J. Intell. Unmanned Syst. 6(1), 32–46 (2018)
Tuan, D.T., Anh, H.: Visual-GPS combined ‘follow-me’ tracking for selfie drones. Adv. Robot. 32(19), 1047–1060 (2018)
Peng, K., et al.: A hybrid genetic algorithm on routing and scheduling for vehicle-assisted multi-drone parcel delivery. IEEE Access 7(1), 2169–3536 (2019)
Pollin, S., Bergh, B.V.: Keeping UAVs under control during GPS jamming. IEEE Syst. J. 13(2), 2010–2021 (2019)
Chiang, W.C., Li, Y., Shang, J., Urban, T.L.: Impact of drone delivery on sustainability and cost: realizing the UAV potential through vehicle routing optimization. Appl. Energy 242(2019), 1164–1175 (2019)
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Shrestha, A., Ali, S.I., Alwan, A.A., Salahuddin, A.E., Siddiqi, M., Rashid, T.A. (2022). GPS Navigated Drones to Deliver Emergency Medical Aid Post Catastrophic Event. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the ICR’22 International Conference on Innovations in Computing Research. ICR 2022. Advances in Intelligent Systems and Computing, vol 1431. Springer, Cham. https://doi.org/10.1007/978-3-031-14054-9_9
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