Elizaveta Isianova Wins Werner von Siemens Award 2025, Lukáš Vítek Ranks Among Top 5
The RICAIP Testbed Prague is proud to celebrate another outstanding achievement. Elizaveta Isianova, a recent graduate and applied researcher at the Czech Institute of Informatics, Robotics, and Cybernetics at Czech Technical University in Prague (CIIRC CTU), while her colleague from RICAIP Testbed Prague Lukáš Vítek ranked among the TOP 5 works in the same category.
Elizaveta Isianova: 1st Place (Industry 4.0)
Elizaveta completed her Master’s degree in Robotics and Cybernetics at the Faculty of Electrical Engineering at CTU, building on her Bachelor’s in Cybernetics and Robotics. She joined Testbed in 2021 as a junior researcher. For her master thesis, she worked closely with Varun Burde, Ph.D. candidate and Testbed researcher, who supervised her master thesis and provided crucial guidance in integrating advanced AI methods into practical robotics.
Her award-winning project addresses a long-standing challenge in industrial robotics – enabling robots to manipulate unfamiliar objects without the need for time-consuming manual programming. Elizaveta applied visual-language models to enable semantic grasping, allowing robots to understand functional parts of objects and perform zero-shot manipulation.
Lukáš Vítek: TOP 5 (Industry 4.0)
Lukáš Vítek, a graduate of Robotics in the Robotics and Manufacturing Technology program at the Faculty of Mechanical Engineering at the Czech Technical University in Prague, was recognized among the TOP 5 works in the Industry 4.0 category at the Werner von Siemens Award 2025.
His master’s thesis, supervised by Petr Beneš, Ph.D., focused on the implementation of visual servoing for robotic manipulation. The system enables a robotic arm to continuously observe an object using a camera and adjust its movement in real time, rather than relying on a fixed trajectory planned in advance. Unlike conventional robotic manipulation approaches, which operate on the assumption that objects remain stationary, Lukáš’s solution allows robots to respond dynamically to changes in the environment. This capability is particularly valuable for flexible production systems, where objects or conditions may change during operation.