Route planning for multiple unmanned aerial vehicles

• Autorzy: Aguiar Antônio Lucas Sousa Aguiar , Pinto Vandilberto P. , Sousa Lígia Maria Carvalho , Pinheiro José Lucas Da Silva , do Nascimento José Cleilton

Identyfikatory

DOI

10.15199/48.2024.09.43

Warianty tytułu

PL

Planowanie trasy dla wielu bezzałogowych statków powietrznych

• Języki publikacji: EN

Abstrakty

EN

This study addresses efficient task assignment for collaborative systems, with a focus on route planning for multiple Unmanned Aerial Vehicles (UAVs). Using the Ant Colony Optimization algorithm and the A* algorithm for obstacle avoidance, the results show that the proposed method allows route planning with acceptable computational time, providing guidance on the optimal number of UAVs in a mission.

PL

Niniejsze badanie dotyczy efektywnego przydzielania zadań dla systemów współpracujących, ze szczególnym uwzględnieniem planowania trasy dla wielu bezzałogowych statków powietrznych (UAV). Wykorzystując algorytm optymalizacji kolonii mrówek i algorytm A* do omijania przeszkód, wyniki pokazują, że proponowana metoda umożliwia planowanie trasy w akceptowalnym czasie obliczeniowym, zapewniając wskazówki dotyczące optymalnej liczby UAV w misji.

Słowa kluczowe

EN

multiple traveling salesmen; UAVs; route planning; ant colony; integer linear programming; circumvent obstacle

PL

wielu podróżujących sprzedawców; UAV; planowanie trasy; kolonia mrówek; programowanie liniowe; omijanie przeszkód

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 9
• Strony: 219--223
• Opis fizyczny: Bibliogr. 17 poz., rys., tab.

Twórcy

autor

Aguiar Antônio Lucas Sousa Aguiar

• Federal University of Ceará

autor

Pinto Vandilberto P.

• University of International Integration of Afro-Brazilian Lusophony

autor

Sousa Lígia Maria Carvalho

• University of International Integration of Afro-Brazilian Lusophony

autor

Pinheiro José Lucas Da Silva

• University of International Integration of Afro-Brazilian Lusophony

autor

do Nascimento José Cleilton

• University of International Integration of Afro-Brazilian Lusophony

Bibliografia

• [1] Bai, X., Jiang, H., Cui, J., Lu, K., Chen, P., & Zhang, M. (2021). UAV Path Planning Based on Improved A* and DWA Algo rithms. International journal of aerospace engineering, 2021.
• [2] De Castro Pereira, S., Solteiro Pires, E. J., & de Moura Oliveira, P. B. (2023). Ant-Balanced Multiple Traveling Sales men: ACO-BmTSP. Algorithms, 16(1), 37.
• [3] Farlei J. Heinen, F. S. O. (2002). Sistema de controle híbrido para robôs móveis autônomos.
• [4] Floreano, Dario, and Robert J Wood.: Science, technol ogy and the future of small autonomous drones. Nature vol. 521,7553 (2015): 460-6. doi:10.1038/nature14542.
• [5] Freitas, E. and Carvalho, J. (2015). Genetic algorithm ap proach for a class of multicriteria, multi-vehicle planner of uavs. volume 9019, pages 234—248.
• [6] Gonçalves, M. A. (2013). Algoritmo a-estrela de estado híbrido aplicado à navegação autônoma de veículos.
• [7] Ju, C. and Son, H. I. (2018). Multiple uav systems for agri cultural applications: Control, implementation, and evaluation. Electronics, 7(9):162.
• [8] Liu, Y., Zhang, Y., Zhang, W., Zhang, Y., and Zhang, J. (2019). Reinforcement learning in multiple-uav networks: Deployment and movement design. IEEE Transactions on Vehicular Tech nology, 68(8):8037–8049.
• [9] Lu, L.-C. and Yue, T.-W. (2017). Mission-oriented ant-team aco for min-max mtsp. In 2017 International Conference on Information, Communication and Engineering (ICICE), pages 522–525. Necula, R., Breaban, M., and Raschip, M. (2015). Tackling the bi-criteria facet of multiple traveling salesman problem with ant colony systems. In 2015 IEEE 27th Interna tional Conference on Tools with Artificial Intelligence (ICTAI).
• [10] M. Dorigo, V. Maniezzo and A. Colorni.: Ant system: optimiza tion by a colony of cooperating agents, in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 26, no. 1, pp. 29-41, Feb. 1996, doi: 10.1109/3477.484436.
• [11] Necula, R., Breaban, M., and Raschip, M. (2015).: Tackling the bi-criteria facet of multiple traveling salesman problem with ant colony systems. In 2015 IEEE 27th International Confer ence on Tools with Artificial Intelligence (ICTAI).
• [12] Niu, C., Li, A., Huang, X., Li, W., and Xu, C. (2021). Research on global dynamic path planning method based on improved a algorithm. Mathematical Problems in Engineering, 2021.
• [13] Pinto, V., Galvão, R., Rodrigues, L., and Gomes, J. P. (2020). Mission planning for multiple uavs in a wind field with flight time constraints. Journal of Control, Automation and Electrical Systems, 31.
• [14] Santana, K. (2020). Método metaheurístico multi-objetivo para o cálculo de rotas de robôs colaborativos com restrições en ergéticas.
• [15] Wang, M., Ma, T., Li, G., Zhai, X., and Qiao, S. (2020). Ant colony optimization with an improved pheromone model for solving mtsp with capacity and time window constraint. IEEE Access, 8:106872–106879.
• [16] Wang, S., Liu, Y., Qiu, Y., Zhang, Q., Huo, F., Huangfu, Y., Yang, C., and Zhou, J. (2022). Cooperative task allocation for multi-robot systems based on multi-objective ant colony sys tem. IEEE Access, 10:56375–56387.
• [17] Wang, Z., Xiang, X., Yang, J., Yang, S. (2017, December). Composite Astar and B-spline algorithm for path planning of autonomous underwater vehicle. In 2017 IEEE 7th Interna tional Conference on Underwater System Technology: Theory and Applications (USYS) (pp. 1-6). IEEE.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).