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conference paper

Learning adaptive movements from demonstration and self-guided exploration

Bruno, D.
•
Calinon, S.
•
Caldwell, D. G.
2014
4th International Conference on Development and Learning and on Epigenetic Robotics
IEEE Intl Conf. on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob)

The combination of imitation and exploration strategies is used in this paper to transfer sensory-motor skills to robotic platforms. The aim is to be able to learn very different tasks with good generalization capabilities and starting from a few demonstrations. This goal is achieved by learning a task-parameterized model from demonstrations where a teacher shows the task corresponding to different possible values of preassigned parameters. In this manner, new reproductions can be generated for new situations by assigning new values to the parameters, thus achieving very precise generalization capabilities. In this paper we propose a novel algorithm that is able to learn the model together with its dependence from the task-parameters, without specifying a predefined relationship or structure. The algorithm is able to learn the model starting from a few demonstrations by applying an exploration strategy that refines the learnt model autonomously. The algorithm is tested on a reaching task performed with a Barrett WAM manipulator.

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Type
conference paper
DOI
10.1109/DEVLRN.2014.6982961
Author(s)
Bruno, D.
•
Calinon, S.
•
Caldwell, D. G.
Date Issued

2014

Published in
4th International Conference on Development and Learning and on Epigenetic Robotics
Start page

101

End page

106

Subjects

learning from demonstration

•

robot learning

•

self-guided exploration

Written at

EPFL

EPFL units
LIDIAP  
Event nameEvent place
IEEE Intl Conf. on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob)

Genoa, Italy

Available on Infoscience
November 19, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/108967
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