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