Our research focuses on designing smart, predictable, and high-performance embedded solutions for next generation Cyber-Physical Systems (CPS). CPS are engineered systems in which computing, communication, and control technologies are tightly integrated and have applications in areas such as system automation, IoT, smart buildings, smart manufacturing, smart cities, digital agriculture, robotics, and autonomous vehicles.
Our research activities include:
- Designing and implementing novel resource management policies for embedded real-time systems running on high-performance heterogeneous platforms
- Developing new reinforcement learning architectures for CPS
- Designing safety architectures towards reliable learning-based controllers in CPS
- Advancing robotics vision systems for industrial production
Our members are also involved in the peer review process of several international conferences and journals in the field of real-time embedded systems and CPS, including RTSS, RTAS, ECRTS, EMSOFT, IROS, ICRA, ICCPS, CDC, ECC, WCNC, ICC, ISCC, GLOBECOM, as well as IEEE Transactions on Computers, IEEE Transactions on Automatic Control, IEEE Transactions on Aerospace and Electronic Systems, IEEE Transactions on Control Systems Technology, ACM Transactions on Cyber-Physical Systems, Real-Time Systems, Journal of System Architectures, IEEE Embedded Systems Letters, IEEE Wireless Communications Letters, IEEE Control Systems Letters, IEEE Sensors Letters, IEEE Systems Journal, IEEE Access, International Journal of Electrical and Computer Engineering, Advances in Space Research.
We are constantly pushing the boundaries of what is possible with CPS and welcome the opportunity to collaborate with fellow research groups and peers.
|Predictable Software Integration on Heterogeneous MultiProcessor System on Chip
|Safety Architectures towards Reliable Learning-based Controllers in CPS
|Simulation Based Learning and Computer Vision for Robotics
|Solar-Powered, Long-Endurance UAV for Real-Time Onboard Data Processing
|Unmanned Aerial Vehicle Database
|IPA2X - Intelligent Pedestrian Assistant to Everyone (EIT UM Project)