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O17    Germany University of Hamburg
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Our objective is to research into the foundations, representations and applications of intelligent systems. This research in computer science is focused on Knowledge Technology and Knowledge Management motivated by natural systems, e.g. biology, cognition and neuroscience. We want to study and exploit nature-inspired, in particular hybrid neural and symbolic representations, in order to build next-generation adaptive knowledge-based systems, learning ambient intelligence systems, multimodal neural agents, self organizing knowledge discovery systems and human robot interaction systems.
 
Research overview
Projects
 
Robotics for Development of Cognition (RobotDoC)
The RobotDoC Collegium is a multi-national doctoral training network for the interdisciplinary training on developmental cognitive robotics. The RobotDoc Fellows develop advanced expertise of domain-specific robotics research skills and of complementary transferrable skills for careers in academia and industry. They acquire hands-on experience through experiments with the open-source humanoid robot iCub, complemented by other existing robots available in the network's laboratories.

Leading Investigator: Prof. Dr. S. Wermter, Dr. C. Weber
Associates: N. Navarro, J. Zhong
Knowledgeable SErvice Robots for Aging (KSERA)
KSERA investigates the integration of assistive home technology and service robotics to support older users in a domestic environment. The KSERA system helps older people, especially those with COPD (a lung disease), with daily activities and care needs and provides the means for effective self-management.

The main aim is to design a pleasant, easy-to-use and proactive socially assistive robot (SAR) that uses context information obtained from sensors in the older person's home to provide useful information and timely support at the right place.

Leading Investigator: Prof. Dr. S. Wermter, Dr. C. Weber
Associates: N. Meins, W. Yan
 
Cross-modal Interaction in Natural and Artificial Cognitive Systems (CINACS)
CINACS is an international graduate colleg that investigates the principles of cross-modal interactions in natural and cognitive systems to implement them in artificial systems. Research will primarily consider the three sensory systems vision, hearing and haptics. This project, accomplished by the University of Hamburg and the University of Tsinghua, Beijing, is funded by the DFG and the Chinese Ministry of Education.

Spokesperson CINACS: Prof. Dr. J. Zhang
Leading Investigator: Prof. Dr. S. Wermter, Dr. C. Weber
Associates: J. Bauer, J. Kleesiek
What it Means to Communicate (NESTCOM)
What does it mean to communicate? Many projects have explored verbal and visual communication in humans as well as motor actions. They have explored a wide range of topics, including learning by imitation, the neural origins of languages, and the connections between verbal and non-verbal communication. The EU project NESTCOM is setting out to analyse these results to contribute to the understanding of the characteristics of human communication, focusing specifically on their relationship to computational neural networks and the role of mirror neurons in multimodal communications.

Leading Investigator: Prof. Dr. S. Wermter
Associates: Dr. M. Knowles, M. Page
 
Midbrain Computational and Robotic Auditory Model for focused hearing (MiCRAM)
This research is a collaborative interdisciplinary EPSRC project to be performed between the University of Newcastle, the University of Hamburg and the University of Sunderland. The overall aim is to study sound processing in the mammalian brain and to build a biomimetic robot to validate and test the neuroscience models for focused hearing.

We collaboratively develop a biologically plausible computational model of auditory processing at the level of the inferior colliculus (IC). This approach will potentially clarify the roles of the multiple spectral and temporal representations that are present at the level of the IC and investigate how representations of sounds interact withauditory processing at that level to focus attention and select sound sources for robot models of focused hearing.

Leading Investigator: Prof. Dr. S. Wermter, Dr. H. Erwin
Associates: Dr. J. Liu, Dr. M. Elshaw
Biomimetic Multimodal Learning in a Mirror Neuron-based Robot (MirrorBot)
This project develops and studies emerging embodied representation based on mirror neurons. New techniques including cell assemblies, associative neural networks, Hebbian-type learning associate visual, auditory and motor concepts. The basis of the research is an examination of the emergence of representations of actions, perceptions, conceptions, and language in a MirrorBot, a biologically inspired neural robot equipped with polymodal associative memory.

Leading Investigator: Prof. Dr. S. Wermter, Dr. Weber
Associates: Dr. M. Elshaw
 

 
The robots we work with
 
NAO
iCub
 
Other robots we have developed or worked with
Webots simulation environment
 
Impressions from the KT Lab
 
KSERA: NAO charging, showing a beamer and approaching to a person
Girlsday 2011: The NAO robot as a platform for neuro-cognitive behaviour
 
Human-Robot Interaction: NAO looking at and talking with a person
 
         

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