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An Efficient Multi-agent Deep Deterministic Policy Gradient-Based 3D Dynamic Coverage Algorithm

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Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology (IoTCIT 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1197))

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Abstract

This work studies the problem of dynamic coverage control of multiple Unmanned Aerial Vehicles (UAVs) in the 3 dimensional (3D) environment. In this work, an efficient multi-agent deep deterministic policy gradient-based dynamic surface coverage (MADDPG-DSC) algorithm is proposed. In MADDPG-DSC, a digital elevation-based surface area calculation method is introduced to effectively allocate the points of interest (PoIs). Next, a cooperative trajectory control policy with multi-agent deep deterministic policy gradient is developed to guide the UAVs. Comparing with existing works, MADDPG-DSC shows better performance in terms of larger coverage rate, higher connectivity and lower energy consumption.

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Wei Zhang, Lei Lei & Lijuan Zhang

Authors
  1. Wei Zhang
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  2. Lei Lei
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  3. Lijuan Zhang
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Corresponding author

Correspondence to Lijuan Zhang .

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Editors and Affiliations

  1. Central South University, Changsha, Hunan, China

    Jian Dong

  2. School of Information Engineering, Shenzhen University, Shenzhen, Guangdong, China

    Long Zhang

  3. School of Information and Control Engineering, China University of Mining and Technolog, Xuzhou, Jiangsu, China

    Deqiang Cheng

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Zhang, W., Lei, L., Zhang, L. (2024). An Efficient Multi-agent Deep Deterministic Policy Gradient-Based 3D Dynamic Coverage Algorithm. In: Dong, J., Zhang, L., Cheng, D. (eds) Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology. IoTCIT 2023. Lecture Notes in Electrical Engineering, vol 1197. Springer, Singapore. https://doi.org/10.1007/978-981-97-2757-5_9

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  • DOI: https://doi.org/10.1007/978-981-97-2757-5_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2756-8

  • Online ISBN: 978-981-97-2757-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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