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.
This work was supported in part by the National Key Research and Development Program of China under Grant No. 2017YFB1301104, and in part by the National Natural Science Foundation of China under Grant No. 61906212 and Grant No. 61802426.
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Wu, W., Li, J., Wu, Y., Ren, X., Tang, Y. (2021). Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree. In: Gao, H., Wang, X., Iqbal, M., Yin, Y., Yin, J., Gu, N. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 350. Springer, Cham. https://doi.org/10.1007/978-3-030-67540-0_32
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