Inspecting Critical Infrastructure such as Power Masts or Railway Tracks with Drones: University of Klagenfurt project receives funding from the Christian Doppler Research Association
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Inspecting Critical Infrastructure such as Power Masts or Railway Tracks with Drones: University of Klagenfurt project receives funding from the Christian Doppler Research Association


Whether dams, power grids, pipelines, railway tracks, or aircraft, the regular inspection of such systems is essential for detecting potential damage at an early stage and preventing costly or hazardous failures. Until now, these inspection processes have typically required considerable human effort and often posed significant safety risks for the personnel involved. With AIONIC (AI-based Object-relative Navigation for Inspection of Critical Infrastructure), the research team seeks to transform this process. As Thomas Jantos explains: “With the help of Artificial Intelligence and novel sensor technologies, drones will in future be capable of navigating independently for extended periods without human intervention and inspecting critical infrastructure autonomously.”

Behind this vision lie several fundamental research challenges. The drones or drone swarms must, using AI-based methods, be able to recognise the objects to be inspected — even if they have not previously been trained on them. In addition, they require precise attitude and position estimation, even in dynamic and complex environments. To further improve efficiency, the project employs multi-agent systems, enabling multiple drones or robots to coordinate their activities flexibly and autonomously. Intelligent data analysis is also essential to detect maintenance requirements and anomalies in the inspected objects.

“Across all these areas, there is still a substantial need for fundamental research in order to achieve fully autonomous, long-duration missions by robotic or drone teams operating entirely without human intervention,” explains Martin Scheiber. The AIONIC team builds upon previous projects conducted by the Control of Networked Systems group, including the FFG-funded MUKISANO project and the EU H2020-funded BugWright2 project. As Eren Allak adds: “These projects have demonstrated that inspection technologies hold significant commercial potential. Some modules have already achieved a high level of technological maturity, yet further fundamental research is required to realise our vision of drones and robots capable of fully autonomous, resilient operation — even over extended deployment periods.”

Fichiers joints
  • Eren Allak, Martin Scheiber und Thomas Jantos (Foto: KK)
Regions: Europe, Austria, United Kingdom
Keywords: Applied science, Engineering, Artificial Intelligence, Grants and new facilities

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