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Perception of cloth in assistive robotic manipulation tasks

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Abstract

Assistive robots need to be able to perform a large number of tasks that imply some type of cloth manipulation. These tasks include domestic chores such as laundry handling or bed-making, among others, as well as dressing assistance to disabled users. Due to the deformable nature of fabrics, this manipulation requires a strong perceptual feedback. Common perceptual skills that enable robots to complete their cloth manipulation tasks are reviewed here, mainly relying on vision, but also resorting to touch and force. The use of such basic skills is then examined in the context of the different cloth manipulation tasks, be them garment-only applications in the line of performing domestic chores, or involving physical contact with a human as in dressing assistance.

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Notes

  1. 1.

    It should be noted that the use of deep neural networks not always entails the need of a costly off-line learning phase: in a cloth manipulation-related but different application, servocontrol learning of the position and deformation of soft material from the 3D point cloud, an online deep learning algorithm is presented in Hu et al. (2019). That is, the mapping between the manipulated and the feedback points of the deformable object is determined while manipulated.

  2. 2.

    https://www.iri.upc.edu/project/show/187.

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Acknowledgements

This work was developed in the context of the project CLOTHILDE (“CLOTH manIpulation Learning from DEmonstrations”), which has received funding from the European Research Council (ERC) under the European Union’s Horizon2020 research and innovation programme (Advanced Grant Agreement No. 741930). This work is supported by the Spanish State Research Agency through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656).

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Correspondence to Carme Torras.

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Jiménez, P., Torras, C. Perception of cloth in assistive robotic manipulation tasks. Nat Comput (2020). https://doi.org/10.1007/s11047-020-09784-5

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Keywords

  • Robotic assistance
  • Robotic cloth manipulation
  • Perception of cloth