Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Structural Representation of VTOL Drone Flight Route using Nested Graph Structure and Analysis of Its Time Attributes

중첩된 그래프 구조를 이용한 VTOL 드론의 비행경로 구조 표현과 시간속성 분석

  • Yeong-Woong Yu (Air Mobility Research Division, Electronics and Telecommunications Research Institute) ;
  • Hanseob Lee (Air Mobility Research Division, Electronics and Telecommunications Research Institute) ;
  • Sangil Lee (Air Mobility Research Division, Electronics and Telecommunications Research Institute) ;
  • Moon Sung Park (Air Mobility Research Division, Electronics and Telecommunications Research Institute) ;
  • Hoon Jung (Air Mobility Research Division, Electronics and Telecommunications Research Institute)
  • 유영웅 (한국전자통신연구원 에어모빌리티연구본부) ;
  • 이한섭 (한국전자통신연구원 에어모빌리티연구본부) ;
  • 이상일 (한국전자통신연구원 에어모빌리티연구본부) ;
  • 박문성 (한국전자통신연구원 에어모빌리티연구본부) ;
  • 정훈 (한국전자통신연구원 에어모빌리티연구본부)
  • Received : 2024.06.08
  • Accepted : 2024.06.14
  • Published : 2024.06.30
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Abstract

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

Keywords

Acknowledgement

This work was supported by Korean Evaluation Institute of Industrial Technology (KEIT) grant funded by the Korea government (MOTIE) (RS-2023-00256794, Development of drone-robot cooperative multimodal delivery technology for cargo with a maximum weight of 40kg in urban areas)

References

  1. Aggarwal, S., and Kumar, N., Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges, Computer Communications, 2020, Vol. 149, pp. 270-299. https://doi.org/10.1016/j.comcom.2019.10.014
  2. Chung, S. H.. Applications of smart technologies in logistics and transport: A review, Transportation Research Part E: Logistics and Transportation Review, 2021, Vol. 153, p. 102455.
  3. Demiane, F., Sharafeddine, S., and Farhat, O., An optimized UAV trajectory planning for localization in disaster scenarios, Computer Networks, 2020, Vol. 179, 107378.
  4. Eskandaripour, H. and Boldsaikhan, E., Last-mile drone delivery: Past, present, and future, Drones, 2023, Vol. 7, No. 2, p. 77.
  5. European Aviation Safety Agency, Concept of Operations for Drones: A Risk Based Approach to Regulation of Unmanned Aircraft, 2015.
  6. Flightworx, How Do Drone Deliveries Work?, March 21, 2024. https://www.flightworx.aero/blog/how-do-drone-deliveries-work.
  7. Gonzalez-R, P. L., Canca, D., Andrade-Pineda, J. L., Calle, M., and Leon-Blanco, J. M., Truck-drone team logistics: A heuristic approach to multi-drop route planning, Transportation Research Part C: Emerging Technologies, 2020, Vol. 114, pp. 657-680. https://doi.org/10.1016/j.trc.2020.02.030
  8. Hong, Y., Kim, S., Kim, Y., and Cha, J., Quadrotor path planning using A* search algorithm and minimum snap trajectory generation, ETRI Journal, 2021, Vol. 43, No. 6, pp. 1013-1023. https://doi.org/10.4218/etrij.2020-0085
  9. KBTX News, Prime Air launches service in College Station, Dec. 24, 2022, https://www.kbtx.com/2022/12/23/prime-air-launches-service-college-station.
  10. Kleinbekman, I. C., Mitici, M. A., and Wei, P., eVTOL arrival sequencing and scheduling for on-demand urban air mobility, 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), 2018, pp. 1-7.
  11. Market.us, Global Drone Package Delivery Market By Component, By Drone Type, By Package size, By Duration, By Operation Mode, By End-Use, By Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, and Forecast 2024-2033, 2024.
  12. Meister, O., Frietsch, N., Ascher, C., and Trommer, G. F., Adaptive path planning for a vtol-uav, 2008 IEEE/ION Position, Location and Navigation Symposium, 2008, pp. 1252-1259.
  13. Qi, N., Wang, W., Ye, D., Wang, M., Tsiftsis, T. A., and Yao, R., Energy-efficient full-duplex UAV relaying networks: Trajectory design for channel-model-free scenarios, ETRI Journal, 2021, Vol. 43, No. 3, pp. 436-446. https://doi.org/10.4218/etrij.2020-0060
  14. Tang, G., Hou, Z., Claramunt, C., and Hu, X., UAV trajectory planning in a port environment, Journal of Marine Science and Engineering, 2020, Vol. 8, No. 8, 592.
  15. Yu, Y.-W., Jung, H., and Bae, H., Integrated GIS Based Logistics Process Monitoring Framework with Convenient Work Processing Environment for Smart Logistics, ETRI Journal, 2015, Vol. 37, No. 2, pp. 306-316. https://doi.org/10.4218/etrij.15.2314.0056
  16. Zhou, H., Xiong, H. L., Liu, Y., Tan, N. D., and Chen, L., Trajectory planning algorithm of UAV based on system positioning accuracy constraints, Electronics, 2020, Vol. 9, No. 2, 250.