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Multi-UAVs Collaborative Path Planning in the Cramped EnvironmentOA北大核心CSTPCD

中文摘要

Due to its flexibility and complementarity, the multiUAVs 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.

Siyuan Feng;Linzhi Zeng;Jining Liu;Yi Yang;Wenjie Song;

School of Automation,Beijing Institute of Technology,Nanjing 210039,China Nanjing Research Institute of Electronics Technology,Nanjing 210039,ChinaSchool of Automation,Beijing Institute of Technology,Nanjing 210039,China Yichang Testing Technique Research Institute,Yichang 443003,ChinaSchool of Automation,Beijing Institute of Technology,Nanjing 210039,ChinaIEEE School of Automation,Beijing Institute of Technology,Nanjing 210039,China

Collision avoidanceconflict resolutionmulti-unmanned aerial vehicles(UAVs)systempath planning

《IEEE/CAA Journal of Automatica Sinica》 2024 (002)

P.529-538 / 10

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。

10.1109/JAS.2023.123945

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