AIC Seminar Series
Acquisition and Use of Environment Models for Household Robots
|Michael Beetz||Technische Universitaet Muenchen||[Home Page]|
Notice: hosted by Benoit Morisset
Date: Monday August 25, 2008 at 15:00
Location: EJ228 (SRI E building) (Directions)
In recent years we have seen tremendous advances in the mechatronic,
sensing and computational infrastructure of robots, enabling them to
act faster, stronger and more accurately than humans do. Yet, when it
comes to accomplishing manipulation tasks in everyday settings, robots
often do not even reach the sophistication and performance of young
children. This is partly due to humans having developed their brains
into computational and control devices that facilitate
knowledge-informed decision making, perspective taking, envisioning
activities and their consequences, and predictive control. Brains
orchestrate these learning and reasoning mechanisms in order to
produce flexible, adaptive, and reliable behavior in real-time.
Household chores are an activity domain where the superiority of the
cognitive mechanisms in the brain and their role in competent activity
control is particularly evident.
In this talk, I will give an overview of the Intelligent Autonomous
Systems groups ongoing research in the excellence cluster "Cognition
for Technical Systems", in which we investigate in an
interdisciplinary endeavor cognitive mechanisms that are to enable
autonomous robots to produce flexible, reliable and high-performance
behavior for everyday manipulation activities. The talk will step
through the "cognitive perception-action loop" for robot control
focusing on the acquisition and use of environment models for
housework as a running example.
Michael Beetz is a professor for Computer Science at the Department of
Informatics of the Technische Universitaet Muenchen and heads the
Intelligent Autonomous Systems group. He is also vice coordinator of
the German national cluster of excellence COTESYS (Cognition for
Technical Systems) where he is also co-coordinator of the research
area Knowledge and Learning.
Michael Beetz received his diploma degree in Computer Science with
distinction from the University of Kaiserslautern. He received his
MSc, MPhil, and PhD degrees from Yale University in 1993, 1994, and
1996 and his Venia Legendi from the University of Bonn in
2000. Michael Beetz was a member of the steering committee of the
European network of excellence in AI planning (PLANET) and
coordinating the research area robot planning. He was also
principal investigator of a number of research projects in the area of
AI-based robot control. His research interests include plan-based
control of robotic agents, knowledge processing and representation for
robots, integrated robot learning, and cognitive perception.
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