Abstract
Unmanned Aerial Vehicles (UAV) routing is transitioning from an emerging topic to a growing research area and one critical aspect of it is the energy consumption of UAVs. This transition induces a need to identify factors, which affects the energy consumption of UAVs and thereby the routing. This paper presents an analysis of different parameters that influence the energy consumption of the UAV Routing Problem. This is achieved by analyzing an example scenario of a single UAV multiple delivery mission, and based on the analysis, relationships between UAV energy consumption and the influencing parameters are shown.
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References
Yakici, E.: Solving location and routing problem for UAVs. Comput. Ind. Eng. 102, 294–301 (2016). https://doi.org/10.1016/j.cie.2016.10.029
Bolton, G.E., Katok, E.: Learning-by-doing in the newsvendor problem a laboratory investigation of the role of experience and feedback. Manuf. Serv. Oper. Manag. 10, 519–538 (2004). https://doi.org/10.1287/msom.1060.0190
Avellar, G.S.C., Pereira, G.A.S., Pimenta, L.C.A., Iscold, P.: Multi-UAV routing for area coverage and remote sensing with minimum time. Sensors (Switzerland) 15, 27783–27803 (2015). https://doi.org/10.3390/s151127783
Khosiawan, Y., Nielsen, I.: A system of UAV application in indoor environment. Prod. Manuf. Res. 4, 2–22 (2016). https://doi.org/10.1080/21693277.2016.1195304
Barrientos, A., Colorado, J., del Cerro, J., et al.: Aerial remote sensing in agriculture: a practical approach to area coverage and path planning for fleets of mini aerial robots. J. Field Robot. 667–689 (2011). https://doi.org/10.1002/rob
Khosiawan, Y., Park, Y., Moon, I., et al.: Task scheduling system for UAV operations in indoor environment. Neural Comput. Appl. 9, 1–29 (2018). https://doi.org/10.1007/s00521-018-3373-9
Khosiawan, Y., Khalfay, A., Nielsen, I.: Scheduling unmanned aerial vehicle and automated guided vehicle operations in an indoor manufacturing environment using differential evolution-fused particle swarm optimization. Int. J. Adv. Robot. Syst. 15, 1–15 (2018). https://doi.org/10.1177/1729881417754145
Bae, H., Moon, I.: Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles. Appl. Math. Model. 40, 6536–6549 (2016)
Zhang, M., Su, C., Liu, Y., et al.: Unmanned aerial vehicle route planning in the presence of a threat environment based on a virtual globe platform. ISPRS Int. J. Geo Inf. 5, 184 (2016). https://doi.org/10.3390/ijgi5100184
Tulum, K., Durak, U., Ider, S.K.: Situation aware UAV mission route planning. In: Proceedings of the IEEE Aerospace Conference (2009). https://doi.org/10.1109/AERO.2009.4839602
Thibbotuwawa, P., Peter, I., Zbigniew, B., Bocewicz, G.: Energy consumption in unmanned aerial vehicles: a review of energy consumption models and their relation to the UAV routing. In: 38th International Conference “Information Systems Architecture and Technology” (2018, to appear)
Dang, Q.V., Nielsen, I., Steger-Jensen, K., Madsen, O.: Scheduling a single mobile robot for part-feeding tasks of production lines. J. Intell. Manuf. 25, 1271–1287 (2014). https://doi.org/10.1007/s10845-013-0729-y
Nielsen, I., Dang, Q.V., Bocewicz, G., Banaszak, Z.: A methodology for implementation of mobile robot in adaptive manufacturing environments. J. Intell. Manuf. 28, 1171–1188 (2017). https://doi.org/10.1007/s10845-015-1072-2
Dang, Q.V., Nielsen, I.: Simultaneous scheduling of machines and mobile robots. Commun. Comput. Inf. Sci. 365, 118–128 (2013). https://doi.org/10.1007/978-3-642-38061-7_12
Visoldilokpun, S.: UAV routing problem with limited risk. The University of Texas at Arlington (2008)
Biradar, A.S.: Wind estimation and effects of wind on waypoint navigation of UAVs. Masters thesis, Arizona State University (2014). https://repository.asu.edu/attachments/135075/content/Biradar_asu_0010N_13909.pdf
Huang, Y., Zhao, L., Van Woensel, T., Gross, J.P.: Time-dependent vehicle routing problem with path flexibility. Transp. Res. Part B Methodol. 95, 169–195 (2017). https://doi.org/10.1016/j.trb.2016.10.013
Taş, D., Gendreau, M., Jabali, O., Laporte, G.: The traveling salesman problem with time-dependent service times. Eur. J. Oper. Res. 248, 372–383 (2016). https://doi.org/10.1016/j.ejor.2015.07.048
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Thibbotuwawa, A., Nielsen, P., Zbigniew, B., Bocewicz, G. (2019). Factors Affecting Energy Consumption of Unmanned Aerial Vehicles: An Analysis of How Energy Consumption Changes in Relation to UAV Routing. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018. ISAT 2018. Advances in Intelligent Systems and Computing, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-99996-8_21
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DOI: https://doi.org/10.1007/978-3-319-99996-8_21
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