Project Details
Projekt
EXC 142: Cognition for Technical Systems (CoTeSys)
Subject Area
Systems Engineering
Computer Science
Computer Science
Term
from 2006 to 2014
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 25268764
The CoTeSys cluster of excellence investigates cognition for technical systems such as vehicles, robots, and factories. Cognitive technical systems are information processing systems equipped with artificial sensors and actuators, integrated and embedded into physical systems, and acting in a physical world. They differ from other technical systems as they perform cognitive control and have cognitive capabilities. Cognitive control orchestrates reflexive and habitual behaviour in accord with long-term intentions. Cognitive capabilities such as perception, reasoning, learning, and planning turn technical systems into systems that "know what they are doing". The cognitive capabilities will result in systems of higher reliability, flexibility, adaptivity, and better performance.
They will be easier to interact and cooperate with. To this end, cognitive scientists investigate the neurobiological and neurocognitive foundations of cognition in humans and animals and develop computational models of cognitive capabilities that explain their empirical findings. These computational models will then be studied by the CoTeSys engineers and computer scientists with respect to their applicability to artificial cognitive systems and empirically evaluated in the context of the CoTeSys demonstrators, including humanoid robots, autonomous vehicles, and cognitive factories.
CoTeSys structures interdisciplinary research on cognition in three closely intertwined research threads, which perform fundamental research and empirically study and implement cognitive models in the context of the demonstration testbeds. The research threads are:
(1) Systemic neuroscience, cognitive science, and neurocognitive psychology which develop computational models of cognitive control, perception, and motor action based on experimental studies at the behavioural and brain level.
(2) Information processing technology, which studies and develops algorithms and software systems for realizing cognitive capabilities. Particularly relevant are modern methods from control and information theory, artificial intelligence including learning, perception, and symbolic reasoning.
(3) Engineering technologies, which investigate research problems in the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning needed to implement robust cognitive abilities in technical systems with guaranteed performance constraints.
They will be easier to interact and cooperate with. To this end, cognitive scientists investigate the neurobiological and neurocognitive foundations of cognition in humans and animals and develop computational models of cognitive capabilities that explain their empirical findings. These computational models will then be studied by the CoTeSys engineers and computer scientists with respect to their applicability to artificial cognitive systems and empirically evaluated in the context of the CoTeSys demonstrators, including humanoid robots, autonomous vehicles, and cognitive factories.
CoTeSys structures interdisciplinary research on cognition in three closely intertwined research threads, which perform fundamental research and empirically study and implement cognitive models in the context of the demonstration testbeds. The research threads are:
(1) Systemic neuroscience, cognitive science, and neurocognitive psychology which develop computational models of cognitive control, perception, and motor action based on experimental studies at the behavioural and brain level.
(2) Information processing technology, which studies and develops algorithms and software systems for realizing cognitive capabilities. Particularly relevant are modern methods from control and information theory, artificial intelligence including learning, perception, and symbolic reasoning.
(3) Engineering technologies, which investigate research problems in the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning needed to implement robust cognitive abilities in technical systems with guaranteed performance constraints.
DFG Programme
Clusters of Excellence
Applicant Institution
Technische Universität München (TUM)
Participating Institution
Max-Planck-Institut für Neurobiologie (MPIN) (aufgelöst); Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Standort Oberpfaffenhofen
Standort Oberpfaffenhofen
Participating University
Ludwig-Maximilians-Universität München; Universität der Bundeswehr München
Spokesperson
Professor Dr.-Ing. Martin Buss
Participating Researchers
Professor Michael Beetz, Ph.D.; Professor Dr. Alexander Borst; Professor Dr. Gordon Cheng; Professor Dr. Jörg Conradt; Professor Dr. Daniel Cremers; Professor Dr.-Ing. Heiner Deubel; Professor Dr.-Ing. Klaus Diepold; Professorin Dr. Nina Jael Gantert; Professor Dr.-Ing. Stefan Glasauer; Professorin Dr.-Ing. Sandra Hirche; Professorin Dr. Alexandra Kirsch; Professor Dr. Martin Kleinsteuber; Professor Dr. Matthias Kranz; Professor Dr.-Ing. Kolja Ernst Kühnlenz; Professorin Dr. Dongheui Lee; Professor Dr. Hannes Leitgeb; Professor Dr. Hermann J. Müller; Professor Dr. Erich Schneider; Professorin Dr. Kristina Shea; Professor Dr.-Ing. Eckehard Steinbach; Professor Dr.-Ing. Heinz Ulbrich; Professor Dr. Boris Vexler; Professorin Dr.-Ing. Birgit Vogel-Heuser; Privatdozent Dr.-Ing. Dirk Wollherr
