Neurorobotics is an emerging field of research at the intersection of robotics and neuroscience. By embedding simulated models of the brain in robotic bodies, it defines a unique and powerful experimental interface between both disciplines. Brain researchers thereby get access to a novel type of methodology which allows them to evaluate their models during interaction with real-world environments. At the same time, roboticists can directly employ neuroscientific theory for new algorithms and learning methods in robot cognition and control. Research on embodiment further provides strong evidence that the close coupling of neural learning and closed-loop environmental interaction will give way to powerful learning algorithms. The Neurorobotics subproject of the Human Brain Project fosters this synergistic loop by developing both the theory and the tools which will enable scientists and engineers to connect latest state-of-the-art brain simulations to both virtual and physical robots. The results of this research are made publicly available in the Neurorobotics Platform, an advanced robotic simulation environment which offers the interfaces, workflows and tools required to design, execute, and evaluate neurorobotic experiments. The platform integrates and links the theoretical models, brain simulations, neuromorphic chip designs, and supercomputer technology which is developed within the Human Brain Project. This lecture gives an introduction to neurorobotics and highlights future developments in neurorobotic technology. Participants will learn about the huge diversity of neurorobotic research which ranges from early simple models of robot control which are based on only a few neurons to the state-of-the-art closed-loop integration of large-scale brain simulations with detailed models of physical bodies. Based on this overview, the lecture highlights the open challenges in neurorobotics research how they will be addressed in the future development of the Neurorobotics Platform of the Human Brain Project.
Alois C. Knoll received the diploma (M.Sc.) degree in Electrical/Communications Engineering from the University of Stuttgart, Germany, in 1985 and his Ph.D. (summa cum laude) in computer science from the Technical University of Berlin, Germany, in 1988. He served on the faculty of the computer science department of TU Berlin until 1993, when he qualified for teaching computer science at a university (habilitation). He then joined the Technical Faculty of the University of Bielefeld, where he was a full professor and the director of the research group Technical Informatics until 2001. Between May 2001 and April 2004 he was a member of the board of directors of the Fraunhofer-Institute for Autonomous Intelligent Systems. Since autumn 2001 he has been a professor of Computer Science at the Computer Science Department of the Technische Universität München.
His research interests include cognitive, medical and sensor-based robotics, multi-agent systems, data fusion, adaptive systems and multimedia information retrieval. He initiated and was the program chairman of the First IEEE/RAS Conference on Humanoid Robots (IEEE-RAS/RSJ Humanoids2000), he was general chair of IEEE Humanoids2003 and general chair of Robotik 2004, the largest German conference on robotics, and he served on several other organising committees. Prof. Knoll is a member of the German Society for Computer Science and the IEEE.