Open Access Articles

Optimal Multi-UAV Path Planning for Monitoring in Windy Conditions and under Uncertainty

Authors

  • Mohammad Sanjari-Parizi * Department of Industrial Engineering, KN Toosi University of Technology, Tehran, Iran.
  • Hossein Pouralihasani Gohar Zamin Mining and Industrial Company, Sirjan, Iran.
  • Mohammadali Saadati-Parizi Gohar Zamin Mining and Industrial Company, Sirjan, Iran.

https://doi.org/10.22105/raise.v3i1.84

Abstract

Nowadays, due to the advances in Unmanned Aerial Vehicles (UAV) technology, they are used in various applications, including surveillance and imaging of various areas. In this paper, the problem of routing UAVs to image specific areas with different accuracy requirements is investigated. The mission planning was done considering different weather conditions and wind currents, and the uncertainty in wind speed, which affects the final speed of the drone, was investigated. A mathematical model was presented to determine the optimal flight paths of the drones, while taking into account the imaging accuracy that is adjusted by altitude. Computational experiments were performed to investigate the problem and the presented model using the GAMS software.

Keywords

Unmanned aerial vehicle Mission planning Drone Aerial monitoring Vehicle routing problem Mathematical model
References (16)
  1. [1] Zhen, L., Li, M., Laporte, G., & Wang, W. (2019). A vehicle routing problem arising in unmanned aerial monitoring. Computers & operations research, 105, 1–11. https://doi.org/10.1016/j.cor.2019.01.001

  2. [2] Ristorto, G., D’Incalci, P., Gallo, R., Mazzetto, F., & Guglieri, G. (2017). Mission planning for the estimation of the field coverage of unmanned aerial systems in monitoring mission in precision farming. Chemical engineering transactions, 58, 649–654. https://doi.org/10.3303/CET1758109

  3. [3] Merino, L., Caballero, F., Martínez-de Dios, J. R., Ferruz, J., & Ollero, A. (2006). A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires. Journal of field robotics, 23(3–4), 165–184. https://doi.org/10.1002/rob.20108

  4. [4] Alotaibi, K. A., Rosenberger, J. M., Mattingly, S. P., Punugu, R. K., & Visoldilokpun, S. (2018). Unmanned aerial vehicle routing in the presence of threats. Computers & industrial engineering, 115, 190–205. https://doi.org/10.1016/j.cie.2017.10.030

  5. [5] Ramirez-Atencia, C., Bello-Orgaz, G., R-Moreno, M. D., & Camacho, D. (2017). Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms. Soft computing, 21(17), 4883–4900. https://doi.org/10.1007/s00500-016-2376-7

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How to Cite

Sanjari-Parizi, M., Pouralihasani, H. ., & Saadati-Parizi, M. (2026). Optimal Multi-UAV Path Planning for Monitoring in Windy Conditions and under Uncertainty. Research Annals of Industrial and Systems Engineering, 3(1), 65-75. https://doi.org/10.22105/raise.v3i1.84

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