A computer vision line-tracking algorithm for automatic UAV photovoltaic plants monitoring applications

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.