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Cooperative Multi-UAV Conflict Avoidance Planning in a Complex Urban Environment

Author

Listed:
  • Kaiping Wang

    (Department of Civil Engineering, Tsinghua University, Beijing 100084, China)

  • Mingzhu Song

    (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China)

  • Meng Li

    (Department of Civil Engineering, Tsinghua University, Beijing 100084, China)

Abstract

Trajectory planning is of great value and yet challenging for multirotor unmanned aerial vehicle (UAV) applications in a complex urban environment, mainly due to the complexities of handling cluttered obstacles. The problem further complicates itself in the context of autonomous multi-UAV trajectory planning considering conflict avoidance for future city applications. To tackle this problem, this paper introduces the multi-UAV cooperative trajectory planning (MCTP) problem, and proposes a bilevel model for the problem. The upper level is modeled as an extended multiple traveling salesman problem, aiming at generating trajectories based on heuristic framework for multi-UAV task allocation and scheduling and meanwhile considering UAV kinodynamic properties. The lower level is modeled as a holding time assignment problem to avoid possible spatiotemporal trajectory conflicts, where conflict time difference is analyzed based on the proposed state-time graph method. Numerical studies are conducted in both a 1 km 2 virtual city and 12 km 2 real city with a set of tasks and obstacles settings. The results show that the proposed model is capable of planning trajectories for multi-UAV from the system-level perspective based on the proposed method.

Suggested Citation

  • Kaiping Wang & Mingzhu Song & Meng Li, 2021. "Cooperative Multi-UAV Conflict Avoidance Planning in a Complex Urban Environment," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6807-:d:575992
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    References listed on IDEAS

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    1. Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    2. Furini, Fabio & Persiani, Carlo Alfredo & Toth, Paolo, 2016. "The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 38-55.
    3. Ming Liu & Xin Liu & Maoran Zhu & Feifeng Zheng, 2019. "Stochastic Drone Fleet Deployment and Planning Problem Considering Multiple-Type Delivery Service," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    4. Jiyoon Park & Solhee Kim & Kyo Suh, 2018. "A Comparative Analysis of the Environmental Benefits of Drone-Based Delivery Services in Urban and Rural Areas," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
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    Cited by:

    1. Sicong Yu & Huiji Zheng & Caihong Ma, 2022. "MEC-Enabled Fine-Grained Task Offloading for UAV Networks in Urban Environments," Sustainability, MDPI, vol. 14(21), pages 1-22, October.

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