研究目的
To develop a real-time correction technique for the ?ight path of a multirotor UAV for PV plants inspections using information coming from additional sensors, particularly cameras, to enhance ?ight monitoring capability and correct GNSS position errors.
研究成果
The proposed vision-based guidance law successfully reduces the number of pictures with incomplete coverage of the target PV row, improving the accuracy of automatic inspection for PV plants. The technique is feasible for real-time application and represents a significant step toward autonomous UAV-based monitoring operations in energy plants.
研究不足
The robustness of vision-based methods against changes in lighting and environmental conditions is a potential limitation. Higher steady-state positioning errors compared to direct visual servoing methods are noted.
1：Experimental Design and Method Selection:
The study employs a vision-based guidance law for UAVs, combining a Canny edge-detector and a Hough transform for line detection.
2：Sample Selection and Data Sources:
A real PV plant configuration in Massa Lombarda, Ravenna, Italy, is used as a case study.
3：List of Experimental Equipment and Materials:
The simulation uses the PX4 autopilot’s ?rmware, Gazebo simulator, and a Yuneec Typhoon H480 hexacopter model with GNSS and camera sensors.
4：Experimental Procedures and Operational Workflow:
The UAV's flight path is corrected in real-time based on images captured by the onboard camera, processed to detect PV rows and adjust the flight path accordingly.
5：Data Analysis Methods:
The effectiveness of the vision-based guidance law is evaluated by comparing the UAV's trajectory with and without the correction mechanism.
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