Pose estimation method for indoor unmanned aerial vehicles in substations
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(1.Zhongshan Power Supply Bureau of Guangdong Power Grid Co., Ltd., Zhongshan 528400, China; 2.School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

Clc Number:

TM930

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    Abstract:

    Indoor unmanned aerial vehicle (UAV) inspection in substations can effectively reduce the intensity of manual inspection operations. Due to high flight accuracy requirements and limited carrying capacity, relying solely on UAV-mounted cameras and inertial measurement unit (IMU) data fusion to determine pose fails to meet precision requirements. Therefore, a multi-vision-inertial navigation fusion framework based on the ubiquitous IoT with existing fixed cameras in the substation is proposed. The images of UAV-mounted cameras for indoor lighting conditions are enhanced and combined with IMU data to obtain preliminary UAV position data. In addition, by deploying quick response (QR) codes on UAVs, the improved perspective?n?point (PnP) algorithm is applied to optimize UAV pose data. After the flight is completed, the cumulative error of IMU in the UAV nest is verified. Experimental results have shown that the deployment and maintenance workload of this method is small, and the flight accuracy is significantly improved compared to relying solely on cameras and IMU data fusion algorithms. It can meet the needs of UAV inspection operations in substations.

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张永挺,韩彦微,林永昌,冯一桐,刘 剑.变电站室内无人机位姿估计方法[J].电力科学与技术学报英文版,2025,40(1):138-145. ZHANG Yongting, HAN Yanwei, LIN Yongchang, FENG Yitong, LIU Jian. Pose estimation method for indoor unmanned aerial vehicles in substations[J]. Journal of Electric Power Science and Technology,2025,40(1):138-145.

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  • Online: March 18,2025
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