Research at the Autonomous Systems Lab (ASL) focusses on autonomous mobile robots for individual mobility, manufacturing, and logistics. We design algorithms for decision making and control that enable the robots to adapt intelligently to their environment and actively learn from their measurement data. In joint academic / industrial research projects, we develop autonomous vehicles, drones, and ships for various applications, with a particular focus on complex environments, dynamic interaction, and safety.

Autonomous systems play an increasingly important role in the field of robotics. Their technical potential is expanding rapidly, as ever powerful microprocessors, sensor systems, communication networks and energy storage is becoming available. They also have an enormous practical potential. They take over tedious or hazardous tasks, where they work better and more reliably than humans. 

One example is autonomous vehicles. They can improve traffic safety, offer individual transportation for blind or elderly people, or they simply free the driver's time. Another example is autonomous medical robots, which can help with monitoring and treating patients.

At IME, our passion is the design of intelligent algorithms for the control of autonomous systems - such as self-learning, predictive, or optimal control. We develop algorithms at the cutting-edge of modern research.

These algorithms are used to help the system with perceiving or understanding its environment, e.g., by learning from sensor data or parameter estimation. Other algorithms help the system to make intelligent decisions, perform motion planning in space and time, or to control its movements. Another important focus point of our work is on providing safety guarantees - an aspect that is particularly relevant for the two main applications we consider, autonomous vehicles and medical robots.