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Dynamic path planning based on improved boundary value problem for unmanned aerial vehicle

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Abstract

When unmanned aerial vehicles (UAVs) track a moving target in complex environment, most path planning methods are difficult to combine real-time calculation and optimality. A real-time path planning method based on boundary value problem (BVP) is studied. First, a grid model of terrain is established based on UAV constraints. Then the structure of receding horizon planning ensures the real-time tracking to moving target, and the path is determined based on BVP in each horizon window. The sub-goal of horizon window is designed by line-of-sight, and the method of updating potential field dynamically and the calculation of flight direction are proposed. By comparison with other methods, the simulation results show that the method can ensure the path smooth and feasible. It can track the moving target in real-time and have some optimality, which is suitable for the mission of UAV to track moving target in complex environment.

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Acknowledgments

This work is supported by National Natural Science Foundation of China under Grant 61503255 and Natural Science Foundation of Liaoning Province under Grant 2015020063. The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation. The authors declare that there is no conflict of interest regarding the publication of this article.

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Authors and Affiliations

  1. School of Automation, Shenyang Aerospace University, South DaoYi Street No.37, ShenBei New District, Shenyang, 10136, Liaoning, China

    Xiao Liang, Guanglei Meng & Xia Chen

  2. Shenyang Institute of Automation, Chinese Academy of Sciences, Nanta Street No.114, Shenhe District, Shenyang, 110016, Liaoning, China

    Haitao Luo

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  1. Xiao Liang
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  2. Guanglei Meng
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  3. Haitao Luo
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  4. Xia Chen
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Correspondence to Xiao Liang.

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Liang, X., Meng, G., Luo, H. et al. Dynamic path planning based on improved boundary value problem for unmanned aerial vehicle. Cluster Comput 19, 2087–2096 (2016). https://doi.org/10.1007/s10586-016-0650-1

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  • DOI: https://doi.org/10.1007/s10586-016-0650-1

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