STUDY OF THE PROBLEM OF OPTIMAL MAINTENANCE OF UNMANNED AERIAL VEHICLES IN CONDITIONS OF A SHORTAGE OF VEHICLES

Denys Medynskyi, Iryna Borets

Abstract


The ways to find the ways of solving the problem of optimal service for unmanned aerial vehicles in the conditions of vehicle shortage are explored.

In the study of theory of optimal control and discrete optimization insufficiently explored the problem of optimal graph coverage by the chains of a fixed pattern with the help of a description system of ordinary differential equations.

With the help of the graph theory investigated the optimization problem of the «Upper Cover» for unmanned aerial vehicles service in the conditions of vehicle shortage has been solved.

Study of the problem relates to the mathematical dependence of transport systems. It can be used for determination of the optimal ratio between the amount of Unmanned Aerial Vehicles and fuel (electricity) reserves used by the Unmanned Aerial Vehicles. The method of solving the problem of determining the weight of the arcs of the graph and the problem of constructing a chain is based on that dependence. Part of the problem is the task of docking. The combinatorial task of choosing a set of stations for servicing points of the initial unmanned aerial vehicles dislocation is based on the dependence mentioned. Effective method for solving the problem of optimal coverage of a graph for supply chains with constraints is developed on the bases of the dependence.

The proposed research methods can significantly reduce the cost of delivery of urgent goods using unmanned aerial vehicles.

The proposed research methods can significantly reduce the cost of delivery of urgent goods using unmanned aerial vehicles. Perspective of further researches is studying of mathematical model of optimal servicing the delivery areas in the conditions of the lack of UAV. The constraints for practical purposes must have a group-theoretical approach to solving optimization problems and be reduced for the constructing an optimal cost matrix analysis. Algebraic approach is used, when there is a need in solving a large set of similar types of optimization problems with different constraints in the right hand side only.

It is possible to apply a heuristic algorithm for solving the problem of optimal UAV service. The problem means optimal coverage of a special graph with chains with restriction on the chain length

Keywords


unmanned aerial vehicle; graph; drone; optimality criterion; algorithm solving method; phase coordinates; functions; supply chains

Full Text:

PDF

References


Sawadsitang, S., Niyato, D., Tan, P.-S., Wang, P. (2019). Joint Ground and Aerial Package Delivery Services: A Stochastic Optimization Approach. IEEE Transactions on Intelligent Transportation Systems, 20 (6), 2241–2254. doi: https://doi.org/10.1109/tits.2018.2865893

Chattopadhyay, D. (1999). Application of general algebraic modeling system to power system optimization. IEEE Transactions on Power Systems, 14 (1), 15–22. doi: https://doi.org/10.1109/59.744462

Budnik, V. S., Dolodarenko, V. A., Doroshkevich, V. K., Fedyakin, A. I. (2000). Kompleksniy podhod k proektirovaniyu letatel'nyh apparatov s uchetom veroyatnostnyh faktorov i elementov planirovaniya primeneniya. Proektirovanie letatel'nyh apparatov i ih sistem. Kyiv: Naukova dumka.

Mehndiratta, M., Kayacan, E. (2019). A constrained instantaneous learning approach for aerial package delivery robots: onboard implementation and experimental results. Autonomous Robots, 43 (8), 2209–2228. doi: https://doi.org/10.1007/s10514-019-09875-y

Li, K. W., Jia, H., Peng, L., Gan, L. (2019). Line-of-sight in operating a small unmanned aerial vehicle: How far can a quadcopter fly in line-of-sight? Applied Ergonomics, 81, 102898. doi: https://doi.org/10.1016/j.apergo.2019.102898

Zoto, J., Musci, M. A., Khaliq, A., Chiaberge, M., Aicardi, I. (2019). Automatic Path Planning for Unmanned Ground Vehicle Using UAV Imagery. Advances in Intelligent Systems and Computing, 223–230. doi: https://doi.org/10.1007/978-3-030-19648-6_26

Pěnička, R., Faigl, J., Saska, M., Váňa, P. (2019). Data collection planning with non-zero sensing distance for a budget and curvature constrained unmanned aerial vehicle. Autonomous Robots, 43 (8), 1937–1956. doi: https://doi.org/10.1007/s10514-019-09844-5

Liu, Y., Qi, N., Yao, W., Liu, Y., Li, Y. (2019). Optimal scheduling for aerial recovery of multiple unmanned aerial vehicles using genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 233 (14), 5347–5359. doi: https://doi.org/10.1177/0954410019842487

Wang, S., Ahmed, Z., Hashmi, M. Z., Pengyu, W. (2019). Cliff face rock slope stability analysis based on unmanned arial vehicle (UAV) photogrammetry. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 5 (4), 333–344. doi: https://doi.org/10.1007/s40948-019-00107-2

Bellman, R. (1955). Dynamic programming and a new formalism in the theory of integral equations. Proceedings of the National Academy of Sciences, 41 (1), 31–34. doi: https://doi.org/10.1073/pnas.41.1.31

Cohen, G., Moller, P., Quadrat, J.-P., Viot, M. (1989). Algebraic tools for the performance evaluation of discrete event systems. Proceedings of the IEEE, 77 (1), 39–85. doi: https://doi.org/10.1109/5.21069

Tarjan, R. E. (1978). Complexity of Combinatorial Algorithms. SIAM Review, 20 (3), 457–491. doi: https://doi.org/10.1137/1020067

Shen, D., Zhang, H., Yu, W., Lu, C., Chen, G., Wei, S. et. al. (2014). Scheduling methods for unmanned aerial vehicle based delivery systems. 2014 IEEE/AIAA 33rd Digital Avionics Systems Conference (DASC). doi: https://doi.org/10.1109/dasc.2014.6979640




DOI: http://dx.doi.org/10.21303/2461-4262.2020.001170

Refbacks

  • There are currently no refbacks.




Copyright (c) 2020 Denys Medynskyi, Irina Borets

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN 2461-4262 (Online), ISSN 2461-4254 (Print)