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Multiple Unmanned Aerial Vehicles Path Planning Based on Collaborative Differential Evolution

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Advances in Swarm Intelligence (ICSI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13969))

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Abstract

In this paper, we propose a collaborative differential evolution algorithm (CODE) to solve the problem of the multiple unmanned aerial vehicles (multi-UAVs) path planning in the three-dimensional (3D) environment. Because the centralized differential evolution algorithm (DE) solves the multi-UAVs path planning problem, the dimension is too high and the amount of computation is too large, CODE divides the entire population of DE into several groups equally, and each group searches in parallel, calculates the individual cost of each UAVs and establishes an information exchange mechanism to calculate the cooperation cost between UAVs, and outputs the path corresponding to a UAV. Experimental results show that the proposed algorithm is significantly better than other comparative algorithms.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Yao Lu & Xiangyin Zhang

  2. Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China

    Yao Lu & Xiangyin Zhang

Authors
  1. Yao Lu
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  2. Xiangyin Zhang
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Corresponding author

Correspondence to Xiangyin Zhang .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Harbin Institute of Technology, Shenzhen, China

    Wenjian Luo

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Lu, Y., Zhang, X. (2023). Multiple Unmanned Aerial Vehicles Path Planning Based on Collaborative Differential Evolution. In: Tan, Y., Shi, Y., Luo, W. (eds) Advances in Swarm Intelligence. ICSI 2023. Lecture Notes in Computer Science, vol 13969. Springer, Cham. https://doi.org/10.1007/978-3-031-36625-3_9

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  • DOI: https://doi.org/10.1007/978-3-031-36625-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36624-6

  • Online ISBN: 978-3-031-36625-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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