An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive

Li, Chunxu; Abdo, Ashraf Fahmy; Li, Shaoxiang; Sienz, Johann

doi:10.3389/fnbot.2020.00030

Journal article 814 views 130 downloads

An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive

Chunxu Li

, Ashraf Fahmy Abdo

, Shaoxiang Li, Johann Sienz

Frontiers in Neurorobotics, Volume: 14

Swansea University Authors: Chunxu Li , Ashraf Fahmy Abdo , Johann Sienz

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DOI (Published version): 10.3389/fnbot.2020.00030

Abstract

With requirements to improve life quality, smart homes, and healthcare have gradually become a future lifestyle. In particular, service robots with human behavioral sensing for private or personal use in the home have attracted a lot of research attention thanks to their advantages in relieving high...

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Published in:	Frontiers in Neurorobotics
ISSN:	1662-5218
Published:	Frontiers Media SA 2020
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa54859
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first_indexed	2020-08-03T13:50:15Z
last_indexed	2020-09-17T03:18:49Z
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spelling	v2 54859 2020-08-03 An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive e6ed70d02c25b05ab52340312559d684 0000-0001-7851-0260 Chunxu Li Chunxu Li true false b952b837f8a8447055210d209892b427 0000-0003-1624-1725 Ashraf Fahmy Abdo Ashraf Fahmy Abdo true false 17bf1dd287bff2cb01b53d98ceb28a31 0000-0003-3136-5718 Johann Sienz Johann Sienz true false 2020-08-03 FGSEN With requirements to improve life quality, smart homes, and healthcare have gradually become a future lifestyle. In particular, service robots with human behavioral sensing for private or personal use in the home have attracted a lot of research attention thanks to their advantages in relieving high labor costs and the fatigue of human assistance. In this paper, a novel force-sensing- and robotic learning algorithm-based teaching interface for robot massaging has been proposed. For the teaching purposes, a human operator physically holds the end-effector of the robot to perform the demonstration. At this stage, the end position data are outputted and sent to be segmented via the Finite Difference (FD) method. A Dynamic Movement Primitive (DMP) is utilized to model and generalize the human-like movements. In order to learn from multiple demonstrations, Dynamic Time Warping (DTW) is used for the preprocessing of the data recorded on the robot platform, and a Gaussian Mixture Model (GMM) is employed for the evaluation of DMP to generate multiple patterns after the completion of the teaching process. After that, a Gaussian Mixture Regression (GMR) algorithm is applied to generate a synthesized trajectory to minimize position errors. Then a hybrid position/force controller is integrated to track the desired trajectory in the task space while considering the safety of human-robot interaction. The validation of our proposed method has been performed and proved by conducting massage tasks on a KUKA LBR iiwa robot platform. Journal Article Frontiers in Neurorobotics 14 Frontiers Media SA 1662-5218 hybrid force/position, teaching by demonstration, dynamic motion primitive, dynamic time warping, gaussian mixture regression 29 6 2020 2020-06-29 10.3389/fnbot.2020.00030 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2024-04-10T14:18:51.5269832 2020-08-03T14:48:06.2609495 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Chunxu Li 0000-0001-7851-0260 1 Ashraf Fahmy Abdo 0000-0003-1624-1725 2 Shaoxiang Li 3 Johann Sienz 0000-0003-3136-5718 4 54859__17837__8493d4aac11f409180a55297688f22d4.pdf 54859.pdf 2020-08-03T14:49:34.3193069 Output 1947976 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution License (CC-BY). true English http://creativecommons.org/licenses/by/4.0/
title	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
spellingShingle	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive Chunxu Li Ashraf Fahmy Abdo Johann Sienz
title_short	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
title_full	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
title_fullStr	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
title_full_unstemmed	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
title_sort	An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive
author_id_str_mv	e6ed70d02c25b05ab52340312559d684 b952b837f8a8447055210d209892b427 17bf1dd287bff2cb01b53d98ceb28a31
author_id_fullname_str_mv	e6ed70d02c25b05ab52340312559d684_*_Chunxu Li b952b837f8a8447055210d209892b427__Ashraf Fahmy Abdo 17bf1dd287bff2cb01b53d98ceb28a31_**_Johann Sienz
author	Chunxu Li Ashraf Fahmy Abdo Johann Sienz
author2	Chunxu Li Ashraf Fahmy Abdo Shaoxiang Li Johann Sienz
format	Journal article
container_title	Frontiers in Neurorobotics
container_volume	14
publishDate	2020
institution	Swansea University
issn	1662-5218
doi_str_mv	10.3389/fnbot.2020.00030
publisher	Frontiers Media SA
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department_str	School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
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description	With requirements to improve life quality, smart homes, and healthcare have gradually become a future lifestyle. In particular, service robots with human behavioral sensing for private or personal use in the home have attracted a lot of research attention thanks to their advantages in relieving high labor costs and the fatigue of human assistance. In this paper, a novel force-sensing- and robotic learning algorithm-based teaching interface for robot massaging has been proposed. For the teaching purposes, a human operator physically holds the end-effector of the robot to perform the demonstration. At this stage, the end position data are outputted and sent to be segmented via the Finite Difference (FD) method. A Dynamic Movement Primitive (DMP) is utilized to model and generalize the human-like movements. In order to learn from multiple demonstrations, Dynamic Time Warping (DTW) is used for the preprocessing of the data recorded on the robot platform, and a Gaussian Mixture Model (GMM) is employed for the evaluation of DMP to generate multiple patterns after the completion of the teaching process. After that, a Gaussian Mixture Regression (GMR) algorithm is applied to generate a synthesized trajectory to minimize position errors. Then a hybrid position/force controller is integrated to track the desired trajectory in the task space while considering the safety of human-robot interaction. The validation of our proposed method has been performed and proved by conducting massage tasks on a KUKA LBR iiwa robot platform.
published_date	2020-06-29T14:18:48Z
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score	11.012924

An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive

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