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Formation control and collision avoidance for multi-UAV systems based on Voronoi partition

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Abstract

This paper deals with the formation control problem of multiple unmanned aerial vehicles (UAVs) with collision avoidance. A distributed formation control and collision avoidance method is proposed based on Voronoi partition and conventional artificial potential field. The collision avoidance is achieved by partitioning the whole space into non-overlapping regions based on Voronoi partition theory, which is taken as the task region to confine the movement of each UAV. The general motion control law is designed based on the conventional artificial potential field. As this often leads to local optimum when two UAVs are going to collide with each other and they may stay still where the repulsive force is adversely equivalent to the attractive force. To address this problem, the destination switch scheme is further proposed to let UAVs switch destinations when they reach the local equilibrium. Finally, the effectiveness of proposed formation control algorithm is validated by simulations and experiments.

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Authors and Affiliations

  1. School of Automation, Northwestern Polytechnical University, Xi’an, 710072, China

    JinWen Hu, Man Wang, ChunHui Zhao, Quan Pan & Chang Du

Authors
  1. JinWen Hu
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  2. Man Wang
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  3. ChunHui Zhao
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  4. Quan Pan
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  5. Chang Du
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Corresponding author

Correspondence to JinWen Hu.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61603303 and 61473230), the Natural Science Foundation of Shaanxi Province (Grant Nos. 2017JM6027 and 2017JQ6005), the China Postdoctoral Science Foundation (Grant No. 2017M610650), the Innovation Development Foundation of Aisheng (Grant No. ASN-IF2015-1502), and the Fundamental Research Funds for the Central Universities (Grant No. 3102017JG02011).

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Hu, J., Wang, M., Zhao, C. et al. Formation control and collision avoidance for multi-UAV systems based on Voronoi partition. Sci. China Technol. Sci. 63, 65–72 (2020). https://doi.org/10.1007/s11431-018-9449-9

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  • DOI: https://doi.org/10.1007/s11431-018-9449-9

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