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Cooperative Transmission Tower Inspection with a Vehicle and a UAV in Urban Areas

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  • Ju Wang

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China)

  • Guoqiang Wang

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • Xiaoxuan Hu

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • He Luo

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • Haiqing Xu

    (Anhui Jiyuan Software CO., Ltd., Hefei 230088, China)

Abstract

To reduce the workload of inspectors and improve the inspection efficiency of urban transmission towers, a new inspection method is proposed in this paper, in which an unmanned aerial vehicle (UAV) and vehicle cooperate with each other. We investigate the cooperative path planning problem of a UAV and a vehicle for transmission tower inspection and develop a new 0–1 integer programming model to address the problem. An odd-even layered genetic algorithm (O-ELGA) is proposed to efficiently solve the model. Finally, the effectiveness of the algorithm is further verified by simulation experiments.

Suggested Citation

  • Ju Wang & Guoqiang Wang & Xiaoxuan Hu & He Luo & Haiqing Xu, 2020. "Cooperative Transmission Tower Inspection with a Vehicle and a UAV in Urban Areas," Energies, MDPI, vol. 13(2), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:326-:d:306849
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    References listed on IDEAS

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    1. Haiyan Cheng & Yongjie Zhai & Rui Chen & Di Wang & Ze Dong & Yutao Wang, 2019. "Self-Shattering Defect Detection of Glass Insulators Based on Spatial Features," Energies, MDPI, vol. 12(3), pages 1-14, February.
    2. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    3. Chiang, Wen-Chyuan & Li, Yuyu & Shang, Jennifer & Urban, Timothy L., 2019. "Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization," Applied Energy, Elsevier, vol. 242(C), pages 1164-1175.
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    Cited by:

    1. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    2. Hailong Huang & Andrey V. Savkin, 2020. "Energy-Efficient Autonomous Navigation of Solar-Powered UAVs for Surveillance of Mobile Ground Targets in Urban Environments," Energies, MDPI, vol. 13(21), pages 1-17, October.
    3. Hailong Huang & Andrey V. Savkin & Wei Ni, 2020. "Energy-Efficient 3D Navigation of a Solar-Powered UAV for Secure Communication in the Presence of Eavesdroppers and No-Fly Zones," Energies, MDPI, vol. 13(6), pages 1-12, March.

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