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Moradi Sizkouhi, Amir Mohammad, Aghaei, Mohammadreza, Karimkhani, Mahdi, Esmailifar, Sayyed Majid. (1404). RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants. نشریه مهندسی عمران امیرکبیر, 1(2), 216-227. doi: 10.22060/aest.2025.5849
Amir Mohammad Moradi Sizkouhi; Mohammadreza Aghaei; Mahdi Karimkhani; Sayyed Majid Esmailifar. "RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants". نشریه مهندسی عمران امیرکبیر, 1, 2, 1404, 216-227. doi: 10.22060/aest.2025.5849
Moradi Sizkouhi, Amir Mohammad, Aghaei, Mohammadreza, Karimkhani, Mahdi, Esmailifar, Sayyed Majid. (1404). 'RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants', نشریه مهندسی عمران امیرکبیر, 1(2), pp. 216-227. doi: 10.22060/aest.2025.5849
Moradi Sizkouhi, Amir Mohammad, Aghaei, Mohammadreza, Karimkhani, Mahdi, Esmailifar, Sayyed Majid. RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants. نشریه مهندسی عمران امیرکبیر, 1404; 1(2): 216-227. doi: 10.22060/aest.2025.5849

RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants

Advances in Energy Sciences and Technologies
دوره 1، شماره 2، آذر 2025، صفحه 216-227
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22060/aest.2025.5849
نویسندگان
Amir Mohammad Moradi Sizkouhi1؛ Mohammadreza Aghaei* 2؛ Mahdi Karimkhani3؛ Sayyed Majid Esmailifar3
1Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
2Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Ålesund, Norway; Department of Sustainable Systems Engineering (INATECH), Albert Ludwigs University of Freiburg, Freiburg, Germany
3Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran
چکیده
This paper presents RoboPV, an innovative embedded software for autonomous aerial monitoring of photovoltaic (PV) plants. RoboPV automates monitoring with features like optimal trajectory planning, image processing, and real-time fault detection through four integrated components: boundary area detection, path planning, dynamic processing, and fault analysis. A specialized encoder-decoder deep learning model processes aerial images to identify plant boundaries, while a unique path planning algorithm ensures complete area coverage. During flights, a neural network analyzes images for automatic fault detection. RoboPV also includes decision-making algorithms for various flight conditions, is compatible with low-power micro-computers, and supports the MAVLink protocol for multi-rotor operations. A six-degrees-of-freedom dynamic model was tested in a SIMULINK environment, achieving 93% accuracy in autonomous inspections of large-scale PV installations.
کلیدواژه‌ها
Photovoltaic (PV) power plant؛ Autonomous aerial monitoring؛ Aerial robots؛ Encoder-decoder architecture؛ RoboPV
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تعداد مشاهده مقاله: 2


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