Best Performer Awards, Roland Mittermeir Award, and Doctoral Thesis Award of the Faculty of Technical Sciences 2024/25

On 5 November, the Best Performer Awards 2024/25, the Roland Mittermeir Prize 2024 and, for the first time, the Dissertation Prize 2024/25 were presented at the University meets Industry: Talents for Carinthia event.

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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

Through its Transfer.Science to Spin-off funding scheme, the Christian Doppler Research Association (CDG) is supporting ten research activities as they take their final steps from fundamental research towards application, with a total of EUR 6.8 million in funding. Among the funded initiatives is AIONIC, a project that aims to enable the fully autonomous inspection of critical infrastructure using drones or robotic systems. The AIONIC project team — Thomas Jantos, Martin Scheiber, and Eren Allak — is led by Professor Stephan Weiss, head of the Control of Networked Systems research group. The team is building on extensive preliminary work from prior research projects.

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Flying to victory with the best drones

Gilbert Tanner is part of the SAPIENCE team at the University of Klagenfurt, a group consisting of six young students and researchers who are working on new approaches to the use of drones in search and rescue operations. However, the student, who is pursuing a Bachelor’s degree in Robotics & Artificial Intelligence, is not only launching drones into the air, but also striving for lofty goals himself: he will soon complete his studies in the shortest possible time and will then move on to pursue a Master’s degree programme at ETH Zurich.

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Robots gain new function: algorithm automatically recognises sensors and their mathematical modelling

Robots need localisation algorithms to figure out where they are. These algorithms usually work with sensor data, which can be used to calculate their position. For engineers and researchers, figuring out how a sensor is built, what format the sensor data is in, and how the sensor is calibrated on a robot can be quite a challenge. Christian Brommer and his team at the Control of Networked Systems research group at the University of Klagenfurt have developed a new method that eliminates the need for all of this: the algorithm automatically recognises the sensor model and calculates important data for localisation.

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