Machine learning requires computer hardware to reliable and efficiently compute estimations for ever more complex and fundamentally incomputable quantities. A research team at MPI for Intelligent Systems in Tübingen develops new algorithms which purposely lower the precision of computations and return an explicit measure of uncertainty over the correct result alongside the estimate. Doing so allows for more flexible management of resources, and increases the reliability of intelligent systems.
An animal's running gait is dynamic, efficient, elegant, and adaptive. We see locomotion in animals as an orchestrated interplay of the locomotion apparatus, interacting with its environment. The Dynamic Locomotion Group at the Max Planck Institute for Intelligent Systems in Stuttgart develops novel legged robots to decipher aspects of biomechanics and neuromuscular control of legged locomotion in animals, and to understand general principles of locomotion.
Brain-computer interfaces (BCIs) provide a new means of communication that does not rely on volitional muscle control. This may provide the capability to locked-in patients, e.g., those suffering from amyotrophic lateral sclerosis, to maintain interactions with their environment. Besides providing communication capabilities to locked-in patients, BCIs may further prove to have a beneficial impact on stroke rehabilitation. In this article, the state-of-the-art of BCIs is reviewed and current research questions are discussed.
There have been numerous speculations in scientific publications and the popular media about wirelessly controlled microrobots (microbots) navigating the human body. Such micro-agents could revolutionize minimally invasive medical procedures. Using physical vapor deposition we grow billions of micron-sized colloidal screw-propellers on a wafer. These chiral mesoscopic screws can be magnetized and moved through solution under computer control. The screw-propellers resemble artificial flagella and are the only ‘microbots’ to date that can be fully controlled in solution at micron length scales.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems