A Computer Vision Line-Tracking Algorithm for Automatic UAV Photovoltaic Plants Monitoring Applications

Gabriele Roggi, Alessandro Niccolai, Francesco Grimaccia and Marco Lovera
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Gabriele Roggi: Politecnico di Milano, Dipartimento di Scienze e Tecnologie Aerospaziali, Via La Masa 34, 20156 Milano, Italy
Alessandro Niccolai: Politecnico di Milano, Dipartimento di Energia, Via Lambruschini 4a, 20156 Milano, Italy
Francesco Grimaccia: Politecnico di Milano, Dipartimento di Energia, Via Lambruschini 4a, 20156 Milano, Italy
Marco Lovera: Politecnico di Milano, Dipartimento di Scienze e Tecnologie Aerospaziali, Via La Masa 34, 20156 Milano, Italy

Energies, 2020, vol. 13, issue 4, 1-15

Abstract: In this paper, the authors propose an UAV-based automatic inspection method for photovoltaic plants analyzing and testing a vision-based guidance method developed to this purpose. The maintenance of PV plants represents a key aspect for the profitability in energy production and autonomous inspection of such systems is a promising technology especially for large utility-scale plants where manned techniques have significant limitations in terms of time, cost and performance. In this light, an ad hoc flight control solution is investigated to exploit available UAV sensor data to enhance flight monitoring capability and correct GNSS position errors with respect to final target needs. The proposed algorithm has been tested in a simulated environment with a software-in-the loop (SITL) approach to show its effectiveness and final comparison with state of the art solutions.

Keywords: PV plant monitoring; Unmanned Aerial Vehicles; automatic flight; image processing; computer vision; fly-by-sensor (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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