Abstract
Fleet mission planning for Unmanned Aerial Vehicles (UAVs) involves creating flight plans for a specific set of objectives, which typically, have to be achieved over a specific time period. The key challenge is to develop methods allowing to prototype mission plans, encompassing UAV routes and schedules, that are robust to changing weather conditions and energy constraints. This paper presents a declarative approach to solving UAV mission planning problems subject to weather uncertainty. The approach was tested using several examples, for which we analyzed how the achievement of mission goals depended on parameters, such as UAV fleet size, UAV energy capacity, weather changes, including wind direction and wind speed, as well as the structure of the distribution network and the time horizon.
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References
Bocewicz, G., Nielsen, P., Banaszak, Z., Thibbotuwawa, A.: Deployment of battery swapping stations for unmanned aerial vehicles subject to cyclic production flow constraints. In: Communications in Computer and Information Science, pp. 73–87. Springer (2018)
Chandran, B., Raghavan, S.: Modeling and solving the capacitated vehicle routing problem on trees. In: The Vehicle Routing Problem: Latest Advances and New Challenges. Springer, pp. 239–261, Boston (2008). https://doi.org/10.1007/978-0-387-77778-8_11
Cho, J., Lim, G., Biobaku, T.: Safety and security management with unmanned aerial vehicle in oil and gas industry. Procedia Manuf. 3, 1343–1349 (2015)
Coelho, B.N., Coelho, V.N., Coelho, I.M.: A multi-objective green UAV routing problem. Comput. Oper. Res. 88, 306–315 (2017). https://doi.org/10.1016/j.cor.2017.04.011
Dorling, K., Heinrichs, J., Messier, G.G., Magierowski, S.: Vehicle routing problems for drone delivery. IEEE Trans. Syst. Man Cybern. Syst. 47, 70–85 (2016)
Goerzen, C., Kong, Z., Mettler, B.: A survey of motion planning algorithms from the perspective of autonomous UAV guidance. J. Intell. Robot. Syst. 57, 65–100 (2010)
Gorecki, T., Piet-Lahanier, H., Marzat, J., Balesdent, M.: Cooperative guidance of UAVs for area exploration with final target allocation. IFAC Proc. 46(19), 260–265 (2013)
Guerriero, F., Surace, R., LoscrÃ, V., Natalizio, E.: A multi-objective approach for unmanned aerial vehicle routing problem with soft time windows constraints. Appl. Math. Model. 38, 839–852 (2014). https://doi.org/10.1016/j.apm.2013.07.002
Habib, D., Jamal, H., Khan, S.A.: Employing multiple unmanned aerial vehicles for co-operative path planning. Int. J. Adv. Robot. Syst. 10, 235 (2013). https://doi.org/10.5772/56286
Kinney, G.W., Hill, R.R., Moore, J.T.: Devising a quick-running heuristic for an unmanned aerial vehicle (UAV) routing system. J. Oper. Res. Soc. 56, 776–786 (2005)
Khosiawan, Y., Nielsen, I., Do, N.A.D., Yahya, B.N.: Concept of Indoor 3D-route UAV scheduling system. In: Proceedings of 36th International Conference on Information Systems Architecture and Technology, pp. 29–40 (2016)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006). http://planning.cs.uiuc.edu. Accessed 13 Jan 2020
Sitek, P., Wikarek, J.: A multi-level approach to ubiquitous modeling and solving constraints in combinatorial optimization problems in production and distribution. Appl. Intell. 48(5), 1344–1367 (2018)
Sitek, P., Wikarek, J.: Capacitated Vehicle Routing Problem with Pick-up and Alternative Delivery (CVRPPAD) – model and implementation using hybrid approach. Ann. Oper. Res. 273(1–2), 257–277 (2019)
Thibbotuwawa, A., Bocewicz, G., Zbigniew, B., Nielsen, P.: A solution approach for UAV fleet mission planning in changing weather conditions. Appl. Sci. 9, 3972 (2019)
Thibbotuwawa, A., Bocewicz, G., Nielsen, P., Zbigniew, B.: Planning deliveries with UAV routing under weather forecast and energy consumption constraints. IFAC-PapersOnLine 52, 820–825 (2019)
Tian, J., Shen, L., Zheng, Y.: Genetic algorithm based approach for multi-UAV cooperative reconnaissance mission planning problem. In: BT—Foundations of Intelligent Systems, pp. 101–110. Springer, Heidelberg (2006)
Tseng, C.M., Chau, C.K., Elbassioni, K., Khonji, M.: Autonomous Recharging and Flight Mission Planning for Battery-operated Autonomous Drones. arXiv (2017)
Xu, K.X.K., Hong, X.H.X., Gerla, M.G.M.: Landmark routing in large wireless battlefield networks using UAVs. In: Proceedings of the MILCOM 2001 Communications for Network-Centric Operations: Creating the Information Force, vol. 1, pp. 230–234 (2001)
Zhen, L., Li, M., Laporte, G., Wang, W.: A vehicle routing problem arising in unmanned aerial monitoring. Comput. Oper. Res. 105, 1–11 (2019). https://doi.org/10.1016/j.cor.2019.01.001
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Radzki, G., Nielsen, P., Bocewicz, G., Banaszak, Z. (2021). UAV Fleet Mission Planning Subject to Robustness Constraints. In: RodrÃguez González, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-53829-3_4
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DOI: https://doi.org/10.1007/978-3-030-53829-3_4
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