The research unit Software-intensive Systems deals with decision-making and optimization issues in loosely coupled, networked and collaborative systems. The increasing networking of systems and the growing complexity of software applications require innovative approaches to enable efficient decision-making and optimization. Ongoing research in this area not only expands technological boundaries, but also creates new opportunities for innovation and progress in various industries and areas of society.

To the research unit Software-intensive Systems

The Systems on Chip research unit deals with fundamental research questions relating to integrated circuits. The current focus of research is primarily on the field of machine learning in embedded systems in order to overcome the challenges of dealing with limited resources. Another promising field of research in the area of SoC is the integration of various sensors and actuators on one chip. This enables the development of highly intelligent, autonomous systems that are able to recognize their environment and react accordingly. Research in this area not only contributes to the further development of hardware, but also enables the emergence of new applications and services that can improve our daily lives and revolutionize the way we interact with technology.

To the research unit Systems on Chip

The Autonomous Systems Lab is engaged in innovative research in the field of cognitive learning and the control of motor skills of robots based on human understanding of movement. The research focuses on two aspects: autonomous learning from observations in daily life and cognitive robot control. In order to realize an intuitive robot and meet people's expectations of a robotic companion, we study human behaviors and transfer the discovered mechanisms to robotic systems. In this way, the robot can learn new skills without engineers having to program it and learn complicated tasks step by step in a generalized framework. In particular, by combining learning from observation, robot motor control and learning from self-experimentation, robots will be able to robustly perform complex tasks under uncertainty.

To the research unit Autonomous Systems