At TUM, the Munich School of Robotics and Machine Intelligence is carrying out cutting-edge interdisciplinary research into AI and robotics for everyday life.
The AI mobility hub "AImotion Bavaria" at the University of Applied Sciences Ingolstadt (THI) has taken over further development of the adaptive mobile manipulator R10-D10. Read on to find out how this AI-enabled, autonomous, and easy-to-program robot learns to optimize production processes in manufacturing.
At THI, guest professor Alessandro Zimmer is strengthening collaborations between Bavaria and Latin America, driving research in AI and mobility engineering across the globe.
Eva Weig and her team are building mechanical quantum sensors large enough to be seen under an electron microscope. One day, they could become fundamental components of a new quantum technology.
Together with industry, researchers at the Technical University Munich (TUM) are shaping the future of work with the new "KI.FABRIK" (AI.Factory) and the German-French Academy for the Industry of the Future (GFA).
At JMU Würzburg, Professor Laurens W. Molenkamp and his team are conducting pioneering work on topological materials. With its cutting-edge technology, the new Institute for Topological Insulators will be the ideal place for them to develop this research.
How much carbon dioxide do parks and individual trees in cities absorb, and how much do they release? To answer this question, researchers at the Technical University of Munich (TUM) have developed a high-resolution CO₂ biogenic flux model. Their findings show that, on average, around two percent of Munich's annual urban emissions are compensated by vegetation. Urban trees have the greatest impact, whereas grassy areas are often net sources of CO₂.
The small satellite SONATE-2 from Würzburg has been in orbit for two years. It completed its mission a year ago; it is still valuable for science and teaching.
- The AI chip is cyber-secure and cloud-independent. - The hardware is based on the RISC-V open-source standard. - The chips are scheduled to be manufactured in Dresden in 2028.
Researchers at the Technical University of Munich (TUM) have developed a method for diagnosing urinary tract infections that significantly accelerates antibiotic resistance testing in urine. Because the procedure does not require labor-intensive pre-cultivation of bacteria – as is standard practice – results on antibiotic effectiveness are available one day earlier. Conventional laboratory analyses require two to three days. The new approach provides the foundation for a home-use rapid test.
