2025/01/24 by Viktor Kozák, Kozák, Viktor, Karel Košnar +7 · 1 citation
Energy · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Power Systems and Renewable Energy #Power Systems and Technologies #Robotics (cs.RO) #Smart Grid and Power Systems
paper · pdf · doi:10.48550/arxiv.2501.14587
openalex publication_date 2025/01/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03
Inspection systems utilizing unmanned aerial vehicles (UAVs) equipped with thermal cameras are increasingly popular for the maintenance of photovoltaic (PV) power plants. However, automation of the inspection task is a challenging problem as it requires precise navigation to capture images from optimal distances and viewing angles. This paper presents a novel localization pipeline that directly integrates PV module detection with UAV navigation, allowing precise positioning during inspection. The detections are used to identify the power plant structures in the image. These are associated with the power plant model and used to infer the UAV position relative to the inspected PV installation. We define visually recognizable anchor points for the initial association and use object tracking to discern global associations. Additionally, we present three different methods for visual segmentation of PV modules and evaluate their performance in relation to the proposed localization pipeline. The presented methods were verified and evaluated using custom aerial inspection data sets, demonstrating their robustness and applicability for real-time navigation. Additionally, we evaluate the influence of the power plant model precision on the localization methods.