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Authors: Abhishek Padalkar 1 ; Matthias Nieuwenhuisen 2 ; Sven Schneider 3 and Dirk Schulz 2

Affiliations: 1 Cognitive Mobile Systems Group, Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE, Wachtberg, Germany, Department of Computer Science, Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany ; 2 Cognitive Mobile Systems Group, Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE, Wachtberg, Germany ; 3 Department of Computer Science, Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany

Keyword(s): Compliant Manipulation, Reinforcement Learning, Task Frame Formalism.

Abstract: Compliant manipulation is a crucial skill for robots when they are supposed to act as helping hands in everyday household tasks. Still, nowadays, those skills are hand-crafted by experts which frequently requires labor-intensive, manual parameter tuning. Moreover, some tasks are too complex to be specified fully using a task specification. Learning these skills, by contrast, requires a high number of costly and potentially unsafe interactions with the environment. We present a compliant manipulation approach using reinforcement learning guided by the Task Frame Formalism, a task specification method. This allows us to specify the easy to model knowledge about a task while the robot learns the unmodeled components by reinforcement learning. We evaluate the approach by performing a compliant manipulation task with a KUKA LWR 4+ manipulator. The robot was able to learn force control policies directly on the robot without using any simulation.

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Paper citation in several formats:
Padalkar, A.; Nieuwenhuisen, M.; Schneider, S. and Schulz, D. (2020). Learning to Close the Gap: Combining Task Frame Formalism and Reinforcement Learning for Compliant Vegetable Cutting. In Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO, ISBN 978-989-758-442-8; ISSN 2184-2809, pages 221-231. DOI: 10.5220/0009590602210231

@conference{icinco20,
author={Abhishek Padalkar. and Matthias Nieuwenhuisen. and Sven Schneider. and Dirk Schulz.},
title={Learning to Close the Gap: Combining Task Frame Formalism and Reinforcement Learning for Compliant Vegetable Cutting},
booktitle={Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO,},
year={2020},
pages={221-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009590602210231},
isbn={978-989-758-442-8},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO,
TI - Learning to Close the Gap: Combining Task Frame Formalism and Reinforcement Learning for Compliant Vegetable Cutting
SN - 978-989-758-442-8
IS - 2184-2809
AU - Padalkar, A.
AU - Nieuwenhuisen, M.
AU - Schneider, S.
AU - Schulz, D.
PY - 2020
SP - 221
EP - 231
DO - 10.5220/0009590602210231

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