Our aim is to leverage on the current state-of-the-art autonomy level to build next-generation smart systems; which execute the given tasks accurately, interact with their environment, collaborate with humans, plan future actions, and adapt new skills through learning processes.
This includes research in control theory, modelling, operations management, identification and simulation of electro-mechanical systems, motion control systems, computer-based real time control systems, adaptive and intelligent semi-autonomous and autonomous systems. Application examples are autonomous ground and aerial systems for smart farming, automotive industry, inspection and maintenance, and logistic systems.
The Artificial Intelligence in Robotics (AiR) group is led by Associate Professor Erdal Kayacan. Our group’s long-term research agenda includes creating a link between control theory (in particular learning control strategies), artificial intelligence, computer vision and robotics.