AERIAL-CORE: AI-Powered Aerial Robots for Inspection and Maintenance of Electrical Power Infrastructures

Anibal Ollero, Alejandro Suarez, Christos Papaioannidis, Ioannis Pitas, Juan M Marredo, Viet Duong, Emad Ebeid, Vit Kratky, Martin Saska, Chloe Hanoune, Amr Afifi, Antonio Franchi, Charalampos Vourtsis, Dario Floreano, Goran Vasiljevic, Stjepan Bogdan, Alvaro Caballero, Fabio Ruggiero, Vincenzo Lippiello, Carlos Matilla, Giovanni Cioffi, Davide Scaramuzza, Jose R Martinez-de-Dios, Begona C Arrue, Carlos Martin, Krzysztof Zurad, Carlos Gaitan, Jacob Rodriguez, Antonio Munoz, Antidio Viguria
January, 2024
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Abstract

Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is crucial to prevent incidents that can significantly affect public safety and the environment. This is especially pertinent in the context of electrical power networks, which, while essential for energy provision, can also be sources of forest fires. Intelligent drones have the potential to revolutionize inspection and maintenance, eliminating the risks for human operators, increasing productivity, reducing inspection time, and improving data collection quality. However, most of the current methods and technologies in aerial robotics have been trialed primarily in indoor testbeds or outdoor settings under strictly controlled conditions, always within the line of sight of human operators. Additionally, these methods and technologies have typically been evaluated in isolation, lacking comprehensive integration. This paper introduces the first autonomous system that combines various innovative aerial robots. This system is designed for extended-range inspections beyond the visual line of sight, features aerial manipulators for maintenance tasks, and includes support mechanisms for human operators working at elevated heights. The paper further discusses the successful validation of this system on numerous electrical power lines, with aerial robots executing flights over 10 kilometers away from their ground control stations.

Type
Preprint
Publication
In ArXiv 2024
Giovanni Cioffi
Giovanni Cioffi
PhD Student

I am a PhD student in Computer Vision and Robotics. My research focuses on perception for autonomous systems.