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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2021 - 8

Wind-Effected Dynamic Quadrotor Route Planning with Metaheuristic Methods in Different Weather Conditions

INCEKARA, H. See more information about INCEKARA, H. on SCOPUS See more information about INCEKARA, H. on IEEExplore See more information about INCEKARA, H. on Web of Science, SELEK, M. See more information about SELEK, M. on SCOPUS See more information about SELEK, M. on SCOPUS See more information about SELEK, M. on Web of Science
 
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Download PDF pdficon (2,136 KB) | Citation | Downloads: 609 | Views: 1,229

Author keywords
genetic algorithms, heuristic algorithms, routing, unmanned aerial vehicles, wind

References keywords
wind(13), unmanned(13), control(13), problem(10), aerial(10), quadrotor(9), vehicle(8), systems(8), routing(8), research(7)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 69 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04008
Web of Science Accession Number: 000725107100008
SCOPUS ID: 85122236431

Abstract
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In cases where quadrotors, which are increasingly important rotary-wing Unmanned Aerial Vehicles (UAVs), are required to visit more than one location, route planning should be done to reduce the cost of flight and increase the efficiency. In this study, it is aimed to reduce the flight time and increase the efficiency of Quadrotor Route Planning (QRP) based on the changes in wind speed and wind angle. To achieve this, a dynamic QRP application which can generate routes which are suitable for changing environmental conditions by using instantaneous wind data and real location coordinates has been developed. In this application, Genetic Algorithm (GA), Tabu Search and Traveling Salesman Problem (TSP) with GA metaheuristic methods were used comparatively to optimize QRP according to flight time. Among these methods, the TSP with GA method is the metaheuristic method that gave the most optimal results. When the results are examined, it is seen that wind effect dynamic QRP that uses TSP and GA method provides up to 26% improvements in flight time compared to Standard QRP that uses TSP with GA method.


References | Cited By  «-- Click to see who has cited this paper

[1] W. P. Coutinho, M. Battarra, J. Fliege, "The unmanned aerial vehicle routing and trajectory optimisation problem, a taxonomic review," Computers & Industrial Engineering, vol. 120, pp. 116-128, 2018.
[CrossRef] [Web of Science Times Cited 111] [SCOPUS Times Cited 134]


[2] D. Stojcsics, A. Molnar, "Fixed-wing small-size UAV navigation methods with HIL simulation for AERObot autopilot," in Intelligent Systems and Informatics (SISY), 2011 IEEE 9th International Symposium on, 2011, pp. 241-245: IEEE.
[CrossRef] [SCOPUS Times Cited 14]


[3] H. Korkmaz, "Development autopilot system on the purpose of tracking and stabilization for fixed wing unmanned aerial vehicle," Master Thesis, Electrical and Electronics Engineering, TOBB ETU University, 2013

[4] N. Sydney, B. Smyth, D. A. Paley, "Dynamic control of autonomous quadrotor flight in an estimated wind field," in 52nd IEEE Conference on Decision and Control, 2013, pp. 3609-3616: IEEE.
[CrossRef]


[5] X. Wang, S. Poikonen, B. Golden, "The vehicle routing problem with drones: Several worst-case results," Optimization Letters, vol. 11, no. 4, pp. 679-697, 2017.
[CrossRef] [Web of Science Times Cited 256] [SCOPUS Times Cited 313]


[6] J. Son, M. Baek, M. Cho, and B. Han, "Multi-object tracking with quadruplet convolutional neural networks," in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 5620-5629.
[CrossRef] [Web of Science Times Cited 149] [SCOPUS Times Cited 192]


[7] C. Ercan, C. Gencer, "Literature review of dynamic unmanned aerial system routing problems and proposals for future studies of UASs," Pamukkale University Journal Of Engineering Sciences, vol. 19, no. 2, pp. 104-111, 2013.
[CrossRef] [Web of Science Times Cited 7]


[8] S. Kim, I. Moon, "Traveling salesman problem with a drone station," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 1, pp. 42-52, 2018.
[CrossRef] [Web of Science Times Cited 149] [SCOPUS Times Cited 161]


[9] M. R. Garey, D. S. Johnson, Computers and intractability. Freeman San Francisco, 1979

[10] J. Chen, F. Ye, Y. Li, "Travelling salesman problem for UAV path planning with two parallel optimization algorithms," in 2017 progress in electromagnetics research symposium-fall (PIERS-FALL), 2017, pp. 832-837.
[CrossRef] [SCOPUS Times Cited 42]


[11] Y. Bouzid, Y. Bestaoui, H. Siguerdidjane, "Guidance-control system of a quadrotor for optimal coverage in cluttered environment with a limited onboard energy: Complete software," Journal of Intelligent & Robotic Systems, vol. 95, no. 2, pp. 707-730, 2019.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 12]


[12] M. Shokouhifar, A. Jalali, H. Torfehnejad, "Optimal routing in traveling salesman problem using artificial bee colony and simulated annealing," in 1st National Road ITS Congress, 2015

[13] B. M. Baker, M. Ayechew, "A genetic algorithm for the vehicle routing problem," Computers & Operations Research, vol. 30, no. 5, pp. 787-800, 2003.
[CrossRef] [Web of Science Times Cited 481] [SCOPUS Times Cited 660]


[14] J. Berger, M. Barkaoui, "A parallel hybrid genetic algorithm for the vehicle routing problem with time windows," Computers & operations research, vol. 31, no. 12, pp. 2037-2053, 2004.
[CrossRef] [Web of Science Times Cited 111] [SCOPUS Times Cited 152]


[15] A. Andreica, C. Chira, "Best-order crossover for permutation-based evolutionary algorithms," Applied Intelligence, vol. 42, no. 4, pp. 751-776, 2015.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 18]


[16] F. Glover, M. Laguna, Tabu search. Springer, Boston, MA, 1997.
[CrossRef]


[17] J. A. Guerrero, J.-A. Escareno, Y. Bestaoui, "Quad-rotor MAV trajectory planning in wind fields," in 2013 IEEE International Conference on Robotics and Automation, 2013, pp. 778-783: IEEE.
[CrossRef] [SCOPUS Times Cited 21]


[18] J. Ware, N. Roy, "An analysis of wind field estimation and exploitation for quadrotor flight in the urban canopy layer," in 2016 IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 1507-1514.
[CrossRef] [SCOPUS Times Cited 49]


[19] Y. Qu, X. Wu, B. Xiao, K. Wang, "Dynamic Modeling and Control of Small-size Quadrotor Considering Wind Field Disturbance," in 2019 Chinese Control And Decision Conference (CCDC), 2019, pp.937-942.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 2]


[20] N. K. Tran, E. Bulka, M. Nahon, "Quadrotor control in a wind field," in 2015 International Conference on Unmanned Aircraft Systems (ICUAS), 2015, pp. 320-328.
[CrossRef] [SCOPUS Times Cited 51]


[21] Y. Lei, H. Wang, "Aerodynamic performance of a quadrotor MAV considering the horizontal wind," IEEE Access, vol. 8, pp. 109421-109428, 2020.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 11]


[22] H. Kim, D. Lim, K. Yee, "Flight control simulation and battery performance analysis of a quadrotor under wind gust," in 2020 International Conference on Unmanned Aircraft Systems (ICUAS), 2020, pp. 1782-1791.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 6]


[23] L. Techy, C. A. Woolsey, "Minimum-time path planning for unmanned aerial vehicles in steady uniform winds," Journal of guidance, control, and dynamics, vol. 32, no. 6, pp. 1736-1746, 2009.
[CrossRef] [Web of Science Times Cited 104] [SCOPUS Times Cited 125]


[24] J. W. Langelaan, N. Alley, J. Neidhoefer, "Wind field estimation for small unmanned aerial vehicles," Journal of Guidance, Control, and Dynamics, vol. 34, no. 4, pp. 1016-1030, 2011.
[CrossRef] [Web of Science Times Cited 157] [SCOPUS Times Cited 213]


[25] S. Waslander, C. Wang, "Wind disturbance estimation and rejection for quadrotor position control," in AIAA Infotech @ Aerospace conference and AIAA unmanned. Unlimited conference, 2009, p. 1983.
[CrossRef] [SCOPUS Times Cited 185]


[26] R. T. Palomaki, N. T. Rose, M. van den Bossche, T. J. Sherman, S. F. De Wekker, "Wind estimation in the lower atmosphere using multirotor aircraft," Journal of Atmospheric and Oceanic Technology, vol. 34, no. 5, pp. 1183-1191, 2017.
[CrossRef] [Web of Science Times Cited 99] [SCOPUS Times Cited 119]


[27] M.-H. Hwang, H.-R. Cha, S. Y. Jung, "Practical endurance estimation for minimizing energy consumption of multirotor unmanned aerial vehicles," Energies, vol. 11, no. 9, p. 2221, 2018.
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 49]


[28] Y.-M. Chen, Y.-l. He, M.-f. Zhou, "Decentralized PID neural network control for a quadrotor helicopter subjected to wind disturbance," Journal of Central South University, vol. 22, no. 1, pp. 168-179, 2015.
[CrossRef] [Web of Science Times Cited 40] [SCOPUS Times Cited 65]


[29] C.-M. Tseng, C.-K. Chau, K. M. Elbassioni, M. Khonji, "Flight tour planning with recharging optimization for battery-operated autonomous drones," CoRR, abs/1703.10049, 2017

[30] A. Thibbotuwawa, G. Bocewicz, G. Radzki, P. Nielsen, Z. Banaszak, "UAV Mission planning resistant to weather uncertainty," Sensors, vol. 20, no. 2, p. 515, 2020.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 61]


[31] H. Luo, Z. Liang, M. Zhu, X. Hu, G. Wang, "Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind," Plos one, vol. 13, no. 3, p. e0194690, 2018.
[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 26]


[32] A. Rucco, A. P. Aguiar, F. L. Pereira, J. B. de Sousa, "A predictive path-following approach for fixed-wing unmanned aerial vehicles in presence of wind disturbances," in Robot 2015: Second Iberian Robotics Conference, 2016, pp. 623-634: Springer.
[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 26]


[33] S. J. Kim, G. J. Lim, J. Cho, "Drone flight scheduling under uncertainty on battery duration and air temperature," Computers & Industrial Engineering, vol. 117, pp. 291-302, 2018.
[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 64]


[34] M. G. Mudurlugu. (2021, 01.02.2021). Meteoroloji Genel Mudurlugu. [Online] Available: Temporary on-line reference link removed - see the PDF document

[35] O. Unsal, T. Yigit, "Yapay zeka ve kumeleme teknikleri kullanilarak geliştirilen yontem ile okul servisi rotalama probleminin optimizasyonu," Muhendislik Bilimleri ve Tasarim Dergisi, vol. 6, no. 1, pp. 7-20, 2018.
[CrossRef]


[36] D. Popescu, F. Stoican, L. Ichim, "Control and optimization of UAV trajectory for aerial coverage in photogrammetry applications," Advances in Electrical and Computer Engineering, vol. 16, no.3, pp.99-106, 2016.
[CrossRef] [Full Text] [Web of Science Times Cited 6] [SCOPUS Times Cited 13]


[37] J.-F. Cordeau, M. Gendreau, G. Laporte, J.-Y. Potvin, F. Semet, "A guide to vehicle routing heuristics," Journal of the Operational Research society, vol. 53, no. 5, pp. 512-522, 2002.
[CrossRef] [SCOPUS Times Cited 442]


[38] M. Eryavuz, C. Gencer, "Arac rotalama problemine ait bir uygulama," Suleyman Demirel Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi, vol. 6, no. 1, pp. 139-155, 2001

[39] G. Laporte, "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, vol. 59, no. 2, pp. 231-247, 1992.
[CrossRef] [Web of Science Times Cited 511] [SCOPUS Times Cited 660]


[40] M. Pulat, I. D. Kocakoc, "Gezgin Satici Probleminin Genetik Algoritmalar Kullanarak Cozumunde Caprazlama Operatorlerinin Ornek Olaylar Bazli Incelenmesi," Izmir Iktisat Dergisi, vol. 34, no. 2, pp. 225-243, 2019.
[CrossRef]


[41] C. Blum, A. Roli, "Metaheuristics in combinatorial optimization: Overview and conceptual comparison," ACM computing surveys (CSUR), vol. 35, no. 3, pp. 268-308, 2003.
[CrossRef] [Web of Science Times Cited 1983] [SCOPUS Times Cited 2520]


[42] J. H. Holland, "Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence," MIT press, 1992.
[CrossRef]


[43] B. Oh, Y. Na, J. Yang, S. Park, J. Nang, J. Kim, "Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication," Advances in Electrical and Computer Engineering, vol.10, no.4, pp.81-86, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 16] [SCOPUS Times Cited 17]


[44] D. J. Bertsimas, P. Jaillet, A. R. Odoni, "A priori optimization," Operations Research, vol. 38, no. 6, pp. 1019-1033, 1990.
[CrossRef] [Web of Science Times Cited 148] [SCOPUS Times Cited 171]


[45] J.-Y. Potvin, "Genetic algorithms for the traveling salesman problem," Annals of Operations Research, vol. 63, no. 3, pp. 337-370, 1996.
[CrossRef] [SCOPUS Times Cited 298]


[46] X. Yu, M. Gen, "Introduction to evolutionary algorithms," Springer Science & Business Media, 2010.
[CrossRef] [Web of Science Times Cited 155]


[47] P. Larranaga, C. M. H. Kuijpers, R. H. Murga, I. Inza, S. Dizdarevic, "Genetic algorithms for the travelling salesman problem: A review of representations and operators," Artificial Intelligence Review, vol. 13, no. 2, pp. 129-170, 1999.
[CrossRef] [Web of Science Times Cited 482] [SCOPUS Times Cited 638]


[48] F. Glover, "Tabu search-part I," ORSA Journal on computing, vol. 1, no. 3, pp. 190-206, 1989.
[CrossRef]


[49] D. Karaboga, Yapay zeka optimizasyon algoritmalari. Nobel Akademi Yayincilik, 2017

[50] N. Akhtar, J. Whidborne, A. Cooke, "Real-time optimal techniques for unmanned air vehicles fuel saving," Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 226, no. 10, pp. 1315-1328, 2012.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 23]


[51] A. Thibbotuwawa, P. Nielsen, B. Zbigniew, G. Bocewicz, "Factors affecting energy consumption of unmanned aerial vehicles: an analysis of how energy consumption changes in relation to UAV routing," in International Conference on Information Systems Architecture and Technology, 2018, pp. 228-238: Springer.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 29]




References Weight

Web of Science® Citations for all references: 5,223 TCR
SCOPUS® Citations for all references: 7,582 TCR

Web of Science® Average Citations per reference: 100 ACR
SCOPUS® Average Citations per reference: 146 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-16 21:57 in 251 seconds.




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