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Flattening Clothes with a Single-Arm Robot Based on Reinforcement Learning

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Intelligent Autonomous Systems 17 (IAS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 577))

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Abstract

Using reinforcement learning has enabled robots to learn how to accomplish a wide range of tasks without explicit instructions. In this paper, we use a single-arm robot for the flattening of a piece of cloth which is crumpled and placed on a table. We create a simulation environment with a gripper and a piece of cloth to learn a policy for the robot to choose the best action based on the observation of the environment. The policy is then transferred to a real robot and successfully tested. We also introduce our method on the recognition of the corners of the cloth using computer vision which includes comparing classic computer vision approach to a deep learning one. We use an ABB robot and a 2D camera for the experiments and PyBullet software for the simulation.

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Authors and Affiliations

  1. Department of Electronics, Informatics and Bio-engineering, Polytechnic University of Milan, Milan, 20133, Italy

    Hassan Shehawy, Daniele Pareyson, Virginia Caruso, Andrea Maria Zanchettin & Paolo Rocco

Authors
  1. Hassan Shehawy
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  2. Daniele Pareyson
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  3. Virginia Caruso
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  4. Andrea Maria Zanchettin
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  5. Paolo Rocco
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Corresponding author

Correspondence to Hassan Shehawy .

Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, University of Zagreb, Zagreb, Croatia

    Ivan Petrovic

  2. Department of Information Engineering, University of Padua, Padua, Italy

    Emanuele Menegatti

  3. Faculty of Electrical Engineering, University of Zagreb, Zagreb, Croatia

    Ivan Marković

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Shehawy, H., Pareyson, D., Caruso, V., Zanchettin, A.M., Rocco, P. (2023). Flattening Clothes with a Single-Arm Robot Based on Reinforcement Learning. In: Petrovic, I., Menegatti, E., Marković, I. (eds) Intelligent Autonomous Systems 17. IAS 2022. Lecture Notes in Networks and Systems, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-031-22216-0_39

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