Reinforcement Learning of Robot Behavior based on a Digital Twin

Tobias Hassel; Oliver Hofmann

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Paper

Reinforcement Learning of Robot Behavior based on a Digital Twin

Topics: Deep Learning and Neural Networks; Industry Related Applications; Machine Learning Methods; Virtual Environments

In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 381-386, 2020 , Valletta, Malta

Authors: Tobias Hassel and Oliver Hofmann

Affiliation: Faculty of Electrical Engineering, Technical University Nuremberg, Keßlerplatz 12, Nuremberg, Germany

Keyword(s): Reinforcement Learning, Digital Twin, Unity.

Abstract: A reinforcement learning approach using a physical robot is cumbersome and expensive. Repetitive execution of actions in order to learn from success and failure requires time and money. In addition, misbehaviour of the robot may also damage or destroy the test bed. Therefore, a digital twin of a physical robot has been used in our research work to train a model within the simulation environment Unity. Later on, the trained model has been transferred to a real-world scenario and used to control a physical agent.

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Paper citation in several formats:

Hassel, T. and Hofmann, O. (2020). Reinforcement Learning of Robot Behavior based on a Digital Twin. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 381-386. DOI: 10.5220/0008880903810386

@conference{icpram20,
author={Tobias Hassel and Oliver Hofmann},
title={Reinforcement Learning of Robot Behavior based on a Digital Twin},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={381-386},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008880903810386},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Reinforcement Learning of Robot Behavior based on a Digital Twin
SN - 978-989-758-397-1
IS - 2184-4313
AU - Hassel, T.
AU - Hofmann, O.
PY - 2020
SP - 381
EP - 386
DO - 10.5220/0008880903810386
PB - SciTePress