Intelligent Vehicle and Robotics Systems Research Group

The objective of the Intelligent Vehicle and Robotics Systems Research Group is the interdisciplinary research and development of advanced vehicle engineering and robotic systems, with particular emphasis on alternative propulsion solutions, real-time control, and new forms of human–machine collaboration.

A key objective of the Research Group is to develop integrated systems that enable the intuitive, human-motion-based control of vehicles and robotic manipulators, as well as a close, real-time connection between physical systems and their digital twins.

The research activities also extend to the development of high-resolution kinematic measurement systems and teleoperation (remote-control) solutions suitable for precision robotic tasks and for the control and investigation of vehicle systems.

The Research Group also aims to publish its research results in high-quality international publications and to strengthen the international visibility of the University’s research in vehicle engineering and robotics.

Leader: 

Dr. Tamás Szakács (Obuda University) 

Members: 

Dr. Ervin  Burkus – (Obuda University-NIK) – expert  

Endre Laguel – (MIAS) – invited expert  

Péter Pintér – (Obuda University -MEI) – expert  

Bence Varga – (Obuda University -MEI) – expert  

Ákos Zsámbok – (Obuda University -MEI) – expert  

Örs Simon – (Obuda University -CHERIATECH) – expert  

Dániel Némedi – (Obuda University -CHERIATECH) – invited expert  

Bálint Klabacsek – (Obuda University -EVRST) – expert  

Bertalan Bihari – (Obuda University – EVRST) – expert  

Zsolt Piukovics – (EMERSON) – invited expert  

Main research areas: 

1. Alternative vehicle propulsion systems: research and development (with particular emphasis on pneumatic propulsion) 

2. Modelling and optimisation of vehicle dynamics and energy systems 

3. Development of teleoperation (remote-control) systems and real-time control architectures 

4. Research on human–machine interfaces and motion-based control systems (e.g. hand-kinematic data gloves) 

5. Development and control of robotic manipulators and anthropomorphic robotic hand systems 

6. Design and implementation of sensor networks and embedded systems 

7. Digital Twin-based systems and real-time simulation environments 

8. Application of machine-learning-based control and prediction methods in vehicle and robotic systems, and brain–computer interfaces (BCI)