Journal of Electronic Science and Technology, Volume. 23, Issue 2, 100303(2025)
Multi-UAV path planning for multiple emergency payloads delivery in natural disaster scenarios
[3] [3] R. Omirgaliyev, N. Zhakiyev, N. Aitbayeva, Y. Akhmetbekov, Application of machine learning methods f the analysis of heat energy consumption by zones with a change in outdo temperature: case study f NurSultan City, Intl. Journal of Sustainable Development Planning 17 (4) (2022) 1247–1257.
[4] [4] K. Ellis, M. Johnson, N. Neogi, J. Homola, NASA research to exp UAS operations f disaster response, in: Proc. of the 34th Congress of the Intl. Council of the Aeronautical Sciences, Flence, USA, 2024, pp. 1–11.
[5] Meng Q.-C., Chen K., Qu Q.-J.. PPSwarm: multi-UAV path planning based on hybrid PSO in complex scenarios. Drones, 8, 192(2024).
[6] [6] W.D. Wu, J.H. Li, Y.L. Wu, X.G. Ren, Y.H. Tang, MultiUAV adaptive path planning in complex environment based on behavi tree, in: Proc. of the 16th EAI Intl. Conf. Collabative Computing: wking, Applications Wksharing, Shanghai, China, 2021, pp. 494–505.
[7] Qiu S.-M., Dai J.-K., Zhao D.-S.. Path planning of an unmanned aerial vehicle based on a multi-strategy improved pelican optimization algorithm. Biomimetics, 9, 647(2024).
[8] Sheng Y.-Y., Liu H.-Y., Li J.-B., Han Q.. UAV autonomous navigation based on deep reinforcement learning in highly dynamic and high-density environments. Drones, 8, 516(2024).
[9] [9] H.X. Pham, H.M. La, D. FeilSeifer, L. Van Nguyen, Reinfcement learning f autonomous UAV navigation using function approximation, in: Proc. of IEEE Intl. Symposium on Safety, Security, Rescue Robotics, Philadelphia, USA, 2018, pp. 1–6.
[12] Poudel S., Moh S.. Priority-aware task assignment and path planning for efficient and load-balanced multi-UAV operation. Veh. Commu., 42, 100633(2023).
[14] [14] Y. Wu, W.L. Fan, W.W. Yang, X.L. Sun, X.R. Guan, Robust trajecty communication design f multiUAV enabled wireless wks in the presence of jammers, IEEE Access 8 (2020) 2893–2905.
[15] Hu G., Zhong J.-Y., Wei G.. SaCHBA_PDN: modified honey badger algorithm with multi-strategy for UAV path planning. Expert Syst. Appl., 223, 119941(2023).
[16] [16] O. Walker, F. Vanegas, F. Gonzalez, S. Koenig, A deep reinfcement learning framewk f UAV navigation in indo environments, in: Proc. of IEEE Aerospace Conf., Big Sky, USA, 2019, pp. 1–14.
[19] Bekhti M., Achir N., Boussetta K., Abdennebi M.. Drone package delivery: a heuristic approach for UAVs path planning and tracking. EAI Endorsed T. Internet of Things, 3, e1(2017).
[22] Hütt C., Bolten A., Hüging H., Bareth G.. UAV LiDAR metrics for monitoring crop height. biomass and nitrogen uptake: a case study on a winter wheat field trial, PFG-J. Photogramm. Rem., 91, 65-76(2023).
[26] [26] H. Ucgun, U. Yuzgec, C. Bayilmis, A review on applications of rotarywing unmanned aerial vehicle ging stations, Int. J. Adv. Robot. Syst. 18 (3) (2021), doi: 10.117717298814211015863.
[27] [27] Z.L. Liu, R. Sengupta, A. Kurzhanskiy, A power consumption model f multirot small unmanned aircraft systems, in: Proc. of Intl. Conf. on Unmanned Aircraft Systems, Miami, USA, 2017, pp. 310–315.
[28] Bai C.-C., Yan P., Yu X.-Q., Guo J.-F.. Learning-based resilience guarantee for multi-UAV collaborative QoS management. Pattern Recogn., 122, 108166(2021).
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Zarina Kutpanova, Mustafa Kadhim, Xu Zheng, Nurkhat Zhakiyev. Multi-UAV path planning for multiple emergency payloads delivery in natural disaster scenarios[J]. Journal of Electronic Science and Technology, 2025, 23(2): 100303
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Received: Sep. 12, 2024
Accepted: Feb. 24, 2025
Published Online: Jun. 16, 2025
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