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Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16–18, 2020, Proceedings, Part II

Research Article

Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree

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  • @INPROCEEDINGS{10.1007/978-3-030-67540-0_32,
        author={Wendi Wu and Jinghua Li and Yunlong Wu and Xiaoguang Ren and Yuhua Tang},
        title={Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree},
        proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part II},
        proceedings_a={COLLABORATECOM PART 2},
        year={2021},
        month={1},
        keywords={Multi-UAV target tracking Behavior tree Real-time path planning},
        doi={10.1007/978-3-030-67540-0_32}
    }
    
  • Wendi Wu
    Jinghua Li
    Yunlong Wu
    Xiaoguang Ren
    Yuhua Tang
    Year: 2021
    Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree
    COLLABORATECOM PART 2
    Springer
    DOI: 10.1007/978-3-030-67540-0_32
Wendi Wu1, Jinghua Li2, Yunlong Wu2,*, Xiaoguang Ren2, Yuhua Tang1
  • 1: State Key Laboratory of High Performance Computing (HPCL), College of Computer, National University of Defense Technology, Changsha
  • 2: Tianjin Artificial Intelligence Innovation Center (TAIIC)
*Contact email: ylwu1988@nudt.edu.cn

Abstract

In this paper, we consider a scenario where multiple tracking unmanned aerial vehicles (UAVs) pursue a target UAV in a complex environment. Consider the fast airspeed of the UAV, the path planning needs to be finished in a limited time. Moreover, the complex environment may involve diverse geographical areas, which raises the challenges for the path planning algorithms. For the first challenge, we will adopt the real-time algorithms to keep the efficiency of path planning. For the challenge of environment diversity, we involve the behavior tree (BT) model and propose a BT-organized path planning (BT-OPP) method aiming at achieving adaptive scheduling of different path planning algorithms in different geographical areas. Furthermore, in order to take the advantages of multiple tracking UAVs, we propose a virtual-target-based tracking (VTB-T) method which can make the tracking UAVs pursue the target UAV collaboratively. The effectiveness of the proposed BT-OPP method and the VTB-T method are verified by analysis and numerical results for different system configurations, showing that a substantial target tracking efficiency improvement may be achieved in comparison with the benchmark.

Keywords
Multi-UAV target tracking Behavior tree Real-time path planning
Published
2021-01-22
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67540-0_32
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