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Intelligent Autonomous Systems Institute
Computer Science Department of the
Technische Universitat Darmstadt
Darmstadt, Germany
Robot Learning Lab
Empirical Inference and Autonomous Motions Depts of the
Max Planck Institute for Intelligent Systems,
Tübingen, Germany
Title: Machine Learning of Motor Skills for Robotics
Slides
Abstract:
Autonomous robots that can assist humans in situations of daily life have
been a long standing vision of robotics, artificial intelligence, and
cognitive sciences. A first step towards this goal is to create robots that
can learn tasks triggered by environmental context or higher level
instruction. However, learning techniques have yet to live up to this
promise as only few methods manage to scale to high-dimensional manipulator
or humanoid robots. In this talk, we investigate a general framework
suitable for learning motor skills in robotics which is based on the
principles behind many analytical robotics approaches. It involves
generating a representation of motor skills by parameterized motor primitive
policies acting as building blocks of movement generation, and a learned
task execution module that transforms these movements into motor commands.
We discuss learning on three different levels of abstraction, i.e., learning
for accurate control is needed to execute, learning of motor primitives is
needed to acquire simple movements, and learning of the task-dependent
"hyperparameters" of these motor primitives allows learning complex tasks.
We discuss task-appropriate learning approaches for imitation learning,
model learning and reinforcement learning for robots with many degrees of
freedom. Empirical evaluations on a several robot systems illustrate the
effectiveness and applicability to learning control on an anthropomorphic
robot arm. These robot motor skills range from toy examples (e.g., paddling
a ball, ball-in-a-cup) to playing robot table tennis against a human being.
Biography:
Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at
the Computer Science Department of the Technische Universitaet Darmstadt and
at the same time a senior research scientist and group leader at the
Max-Planck Institute for Intelligent Systems, where he heads the
interdepartmental Robot Learning Group. Jan Peters has received the Dick
Volz Best 2007 US PhD Thesis Runner Up Award, the Robotics: Science &
Systems - Early Career Spotlight, the INNS Young Investigator Award, and the
IEEE Robotics & Automation Society's Early Career Award.
Jan Peters has studied Computer Science, Electrical, Mechanical and Control
Engineering at TU Munich and FernUni Hagen in Germany, at the National
University of Singapore (NUS) and the University of Southern California
(USC).
He has received four Master's degrees in these disciplines as well as a
Computer Science PhD from USC. Jan Peters has performed research in Germany
at DLR, TU Munich and the Max Planck Institute for Biological Cybernetics
(in addition to the institutions above), in Japan at the Advanced
Telecommunication Research Center (ATR), at USC and at both NUS and Siemens
Advanced Engineering in Singapore.
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