Innovation
Kick-off for the factory of the future: The Munich School of Robotics and Machine Intelligence (MSRM) of the Technical University of Munich (TUM) is starting - as announced by the Bavarian state government in its high-tech agenda - its flagship initiative for the first KI.FABRIK in Bavaria. The KI.FABRIK Bayern is a completely flexible and networked location for the local, crisis-proof and profitable production of the most modern IT and mechatronic high-tech components in Bavaria.
Take part via livestream when the MSRM of TUM lays the foundation stone for the lighthouse initiative KI.FABRIK…
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When we are old, who takes care of us? Because in 30 years the demographic change will be in full swing: 6.1 million people in Germany who need to be cared for and too few people who look after them. That doesn't work. That means we need a solution! One option are robots in care. The Munich School of Robotics and Machine Intelligence team develop robots that could support and relieve the nursing staff. Beta stories shows in this documentary what robots can already do in care and why we will need care robots in the future.
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Get the support you need to implement new effective ways of manufacturing with human-centric industrial robots on your production floor. The European-funded program SHOP4CF (Smart Human Oriented Platform for Connected Factories) offers €100,000 in equity-free funding, expert support, and tailored training sessions on technology, innovation, and finances to each of the winning teams. The call for applications will stay open until August 2021.
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Reflexes protect our bodies – for example when we pull our hand back from a hot stove. These protective mechanisms could also be useful for robots. In this interview, Prof. Sami Haddadin and Johannes Kühn of the Munich School of Robotics and Machine Intelligence (MSRM) of the Technical University of Munich (TUM) explain why giving test subjects a “slap on the hand” could lay the foundations for the robots of the future.
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Alexander König, Gründer von Reactive Robotics, spricht über VEMO, einen Roboter entwickelt, der Intensivpatienten beim Laufen unterstützen soll und die Zusammenarbeit mit der MSRM.
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We have great news: Robothon® – The Grand Challenge 2021 as part of munich_i goes digital!
Apply as a team until 23:59 CEST 30 April 2021 on our website at www.robothon-grand-challenge.com.
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The “Modeling and Rehabilitation Robotics” research team developed a safe and minimalistic control and learning (AI) algorithm, which automatically finds and provides the optimal balance between rigid support and “soft” guidance for any given patient during therapy. This assist-as-needed (AAN) control strategy is being commercialized in collaboration with the high-tech startup Reactive Robotics and Schön Klinik Bad Aibling, as part of a robotic assistive device called VEMO, used for the early rehabilitation of ICU patients.
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TUM Venture Labs aim to strengthen the startup ecosystem and attract more technological capital in the greater Munich area. The initiative offers educational programs, venturing support, and an ecosystem consisting of events, networks, and infrastructure that interdisciplinary teams can use to bring research results and ideas into a viable business venture. One of the many venture labs is the TUM Venture Lab Robotics/AI.
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Ein Forschungsteam der Munich School of Robotics and Machine Intelligence hat ein neues Frühwarnsystem für autonome Fahrzeuge entwickelt, das mit Künstlicher Intelligenz aus Tausenden realen Verkehrssituationen lernt. Eine Studie in Zusammenarbeit mit der BMW Group zeigt, dass das System bei heutigen selbstfahrenden Entwicklungsfahrzeugen bereits sieben Sekunden im Voraus mit mehr als 85 Prozent Genauigkeit vor einer potenziell kritischen Situation warnen kann, die die Autos noch nicht allein meistern können.
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In der Sendung "Xenius: Altersforschung – Darum leben wir immer länger" erläutern Dr. Günter Steinebach (Facharzt für Innere Medizin) und Prof. Sami Haddadin wie der Roboter Garmi in Zukunft ältere Menschen unterstützen und begleiten wird (Minute 11:36-14:40).
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