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A Model-Based Approach to Robot Joint Control (2005)
Daniel Stronger
and
Peter Stone
Despite efforts to design precise motor controllers, robot joints do not always move exactly as desired. This paper introduces a general model-based method for improving the accuracy of joint control. First, a model that predicts the effects of joint requests is built based on empirical data. Then this model is approximately inverted to determine the control requests that will most closely lead to the desired movements. We implement and validate this approach on a popular, commercially available robot, the Sony Aibo ERS-210A.
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Citation:
In
RoboCup-2004: Robot Soccer World Cup VIII
, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 297-309, Berlin 2005. Springer Verlag.
Bibtex:
@incollection{LNAI2004-joints, title={A Model-Based Approach to Robot Joint Control}, author={Daniel Stronger and Peter Stone}, booktitle={RoboCup-2004: Robot Soccer World Cup VIII}, volume={3276}, editor={Daniele Nardi and Martin Riedmiller and Claude Sammut}, series={Lecture Notes in Artificial Intelligence}, address={Berlin}, publisher={Springer Verlag}, pages={297-309}, url="http://www.cs.utexas.edu/users/ai-lab?LNAI2004-joints", year={2005} }
People
Peter Stone
Faculty
pstone [at] cs utexas edu
Daniel Stronger
Ph.D. Alumni
dan stronger [at] gmail com
Areas of Interest
Planning
Robotics
Labs
Learning Agents