The Chair of Mechatronics is characterized by a pioneering combination of physical understanding, mechatronic engineering and scientific machine learning. Our expertise lies in understanding, modelling and optimizing complex interactions between mechanical, electronic and other subsystems. We rely not only on classic methods of physical modeling, but also on innovative approaches from the field of scientific machine learning. Our aim is not only to research new methods and integrate them into the development and optimization of mechatronic systems, but also to increase the performance of these systems in real applications.
Methods developed at our chair aim to be usable for a wide range of applications and are applied to real industrial problems from the automotive, energy and medical sectors for validation.
Students and researchers at our department benefit from the unique opportunity to work in an interdisciplinary environment that combines traditional concepts of mechatronics with the latest developments in machine learning.
Lennart Luttkus is a researcher at the University of Augsburg focusing on autonomous micromobility vehicles and their safety validation. His work bridges simulation frameworks, reinforcement learning, and pedestrian behavior modeling to advance safe and efficient urban mobility. With experience in coordinating interdisciplinary projects such as the Autonomous Driving Lab, he combines technical expertise in AI and robotics with applied research on sustainable transport solutions.