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Volume 11 Issue 2
Feb.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Contents
S. Feng, L. Zeng, J. Liu, Y. Yang, and  W. Song,  “Multi-UAVs collaborative path planning in the cramped environment,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 529–538, Feb. 2024. doi: 10.1109/JAS.2023.123945
Citation: S. Feng, L. Zeng, J. Liu, Y. Yang, and  W. Song,  “Multi-UAVs collaborative path planning in the cramped environment,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 529–538, Feb. 2024. doi: 10.1109/JAS.2023.123945

Multi-UAVs Collaborative Path Planning in the Cramped Environment

doi: 10.1109/JAS.2023.123945
Funds:  This work was partly supported by Program for the National Natural Science Foundation of China (62373052, U1913203, 61903034), Youth Talent Promotion Project of China Association for Science and Technology, Beijing Institute of Technology Research Fund Program for Young Scholars
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  • Due to its flexibility and complementarity, the multi-UAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue (SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles (UAVs) in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search (ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes. The benchmark and source code are released in

    https://github.com/inin-xingtian/multi-UAVs-path-planner

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    Highlights

    • A hierarchical planning framework based on the ECBS algorithm is proposed for multi-UAVs cooperative path planning problem in cramped environments, which has solved the problems of size-constrained obstacle avoidance and spatiotemporal conflict avoidance
    • Relying on the path search algorithm based on the kinematic model of UAVs, the smoothness of output paths is improved, which is convenient for the tracking control of UAVs
    • Detailed experiments are conducted in the specially designed cramped environment test set, and the source code and test set are published, available for comparison by relevant researchers

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