OUR INSTITUTE
The goal of the Max Planck Institute for Intelligent Systems is to investigate and understand the organizing principles of intelligent systems and the underlying perception-action-learning loop. The Max Planck Institute for Intelligent Systems combines – within one center – theory, software, and hardware expertise in the research field of intelligent systems.
The Tübingen campus of the institute focuses on theory and algorithms as well as human-scale systems covering topics such as machine learning, computer vision, control, and the theory of intelligence. Research at the Stuttgart campus of the institute covers small-scale robotics, self-organization, haptic perception, bio-inspired systems, medical robotics, robotic materials and physical intelligence; that is, the embodiment of intelligent behavior in physical, rather than computational, systems.
Intelligent Systems
Every day, artificial intelligence is in the news. Cars are becoming more and more autonomous, unmanned aerial vehicles deliver packages, robots assist us in our homes, and surgery is performed by small robots in our bodies. With the digitization of industry and the presence of cyber-physical systems, Intelligent Systems are increasingly becoming a part of the real world. The ability to create systems for Autonomous Robotics and Intelligent Software is a future key technology in industry, mobility, and our society as a whole.
Intelligent systems operate autonomously in, and adapt to, complex, changing environments. While biological intelligent systems (including humans) have developed sophisticated abilities through interaction, evolution and learning in order to act successfully in our world, our understanding of these phenomena is still limited. The synthesis of intelligent, autonomous, learning systems remains a major scientific challenge. Researchers at the Max Planck Institute for Intelligent Systems investigate the fundamental problem of perception, action, and learning underlying intelligent systems through theoretical and algorithmic work, as well as physical systems on all scales. We want to use this understanding to design future artifically intelligent systems
