Autonomous systems combine the physical capabilities of robots with the intelligence and adaptability provided by AI. Such systems can provide solutions to our urgent societal and environmental challenges, thus promising a better and more sustainable future for our planet and society.

Technology can transform the way we, humans, live and work. Imagine intelligent machines taking care of tasks in our homes and working environments, learning from their mistakes and developing their skills over time.

AUT takes a systems approach to analysis, design and synthesis on automated systems, based on a control theory and associated methodologies. We do research on all levels; in theory, methods, tools and prototypes. Experimental verification is an important element of our research.

Research fields

In the Automation and Control (AUT) group, we perform cutting-edge research in:

• Control Systems and Fault Diagnosis

We are interested in the control of real-world systems where faults and system changes may occur. As a first step, a diagnosis of the system faults or changes is performed, and then, the controller is reconfigured or redesigned based on the information from the diagnosis.

• Perception and Information Processing

For systems and robots to operate autonomously they need to be able to sense their environment and extract meaningful information from sensory data. We are using tools such as AI and signal processing to endow our autonomous systems with robust perception capabilities.

• Systems Engineering and Modularity

A robot or any autonomous system is a very complex system, both in terms of hardware and software, comprising multiple subsystems that need to operate seamlessly together. We take a systems engineering approach and perform research in modular solutions that can make our autonomous systems more robust and easier to develop and maintain.

We combine these topics to create the next generation of truly autonomous systems for the benefit of society.