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Assisting Movement Training and Execution With Visual and Haptic Feedback

Ewerton, Marco and Rother, David and Weimar, Jakob and Kollegger, Gerrit and Wiemeyer, Josef and Peters, Jan and Maeda, Guilherme :
Assisting Movement Training and Execution With Visual and Haptic Feedback.
[Online-Edition]
In: Frontiers in Neurorobotics, 12 ISSN 1662-5218
[Article], (2018)

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Item Type: Article
Title: Assisting Movement Training and Execution With Visual and Haptic Feedback
Language: English
Abstract:

In the practice of motor skills in general, errors in the execution of movements may go unnoticed when a human instructor is not available. In this case, a computer system or robotic device able to detectmovement errors and propose corrections would be of great help. This paper addresses the problem of how to detect such execution errors and how to provide feedback to the human to correct his/her motor skill using a general, principled methodology based on imitation learning. The core idea is to compare the observed skill with a probabilistic model learned from expert demonstrations. The intensity of the feedback is regulated by the likelihood of the model given the observed skill. Based on demonstrations, our system can, for example, detect errors in the writing of characters with multiple strokes. Moreover, by using a haptic device, the Haption Virtuose 6D, we demonstrate a method to generate haptic feedback based on a distribution over trajectories, which could be used as an auxiliary means of communication between an instructor and an apprentice. Additionally, given a performance measurement, the haptic device can help the human discover and performbettermovements to solve a given task. In this case, the human first tries a few times to solve the task without assistance. Our framework, in turn, uses a reinforcement learning algorithm to compute haptic feedback, which guides the human toward better solutions.

Journal or Publication Title: Frontiers in Neurorobotics
Volume: 12
Publisher: Frontiers
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
Divisions: 20 Department of Computer Science
Date Deposited: 10 Jul 2018 14:51
Last Modified: 10 Jul 2018 14:51
DOI: 10.3389/fnbot.2018.00024
Official URL: https://doi.org/10.3389/fnbot.2018.00024
URN: urn:nbn:de:tuda-tuprints-75662
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/7566
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