Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals
Identifieur interne : 000152 ( Pmc/Checkpoint ); précédent : 000151; suivant : 000153Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals
Auteurs : Sébastien Mick [France] ; Daniel Cattaert [France] ; Florent Paclet [France] ; Pierre-Yves Oudeyer [France] ; Aymar De Rugy [France, Australie]Source :
- Frontiers in Neurorobotics [ 1662-5218 ] ; 2017.
Abstract
Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude. With the robotic arm from the open source 3D-printed Poppy Humanoid platform simulating a mobile prosthesis, an experiment was carried out with eighteen able-bodied subjects performing a 3-D target-reaching task using each of the three modes. The subjects were given questionnaires to evaluate the quality of their experience with each mode, providing an assessment of their global usability in the context of the task. According to performance metrics and questionnaire results, velocity control modes were found to perform better than position control mode in terms of accuracy and quality of control as well as user satisfaction and comfort. Subjects also seemed to favor quadratic velocity control over linear (proportional) velocity control, even if these two modes did not clearly distinguish from one another when it comes to performance and usability assessment. These results highlight the need to take into account user experience as one of the key criteria for the design of control modes intended to operate limb prostheses.
Url:
DOI: 10.3389/fnbot.2017.00055
PubMed: 29118699
PubMed Central: 5660981
Affiliations:
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PMC:5660981Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude. With the robotic arm from the open source 3D-printed Poppy Humanoid platform simulating a mobile prosthesis, an experiment was carried out with eighteen able-bodied subjects performing a 3-D target-reaching task using each of the three modes. The subjects were given questionnaires to evaluate the quality of their experience with each mode, providing an assessment of their global usability in the context of the task. According to performance metrics and questionnaire results, velocity control modes were found to perform better than position control mode in terms of accuracy and quality of control as well as user satisfaction and comfort. Subjects also seemed to favor quadratic velocity control over linear (proportional) velocity control, even if these two modes did not clearly distinguish from one another when it comes to performance and usability assessment. These results highlight the need to take into account user experience as one of the key criteria for the design of control modes intended to operate limb prostheses.</p>
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<author><name sortKey="Mackenzie, I S" uniqKey="Mackenzie I">I. S. MacKenzie</name>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Front Neurorobot</journal-id>
<journal-id journal-id-type="iso-abbrev">Front Neurorobot</journal-id>
<journal-id journal-id-type="publisher-id">Front. Neurorobot.</journal-id>
<journal-title-group><journal-title>Frontiers in Neurorobotics</journal-title>
</journal-title-group>
<issn pub-type="epub">1662-5218</issn>
<publisher><publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">29118699</article-id>
<article-id pub-id-type="pmc">5660981</article-id>
<article-id pub-id-type="doi">10.3389/fnbot.2017.00055</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Neuroscience</subject>
<subj-group><subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Mick</surname>
<given-names>Sébastien</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<xref ref-type="corresp" rid="cor1">*</xref>
<uri xlink:type="simple" xlink:href="http://frontiersin.org/people/u/437004"></uri>
</contrib>
<contrib contrib-type="author"><name><surname>Cattaert</surname>
<given-names>Daniel</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Paclet</surname>
<given-names>Florent</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://frontiersin.org/people/u/463350"></uri>
</contrib>
<contrib contrib-type="author"><name><surname>Oudeyer</surname>
<given-names>Pierre-Yves</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://frontiersin.org/people/u/126"></uri>
</contrib>
<contrib contrib-type="author"><name><surname>de Rugy</surname>
<given-names>Aymar</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
<xref ref-type="corresp" rid="cor1">*</xref>
<uri xlink:type="simple" xlink:href="http://frontiersin.org/people/u/244406"></uri>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup>
<institution>Flowers Team, INRIA Bordeaux Sud-Ouest</institution>
,<addr-line>Talence</addr-line>
,<country>France</country>
</aff>
<aff id="aff2"><sup>2</sup>
<institution>Hybrid Team, Institut de Neurosciences Cognitives et Intégratives d’Aquitaine, CNRS UMR 5287, Univ. Bordeaux</institution>
,<addr-line>Bordeaux</addr-line>
,<country>France</country>
</aff>
<aff id="aff3"><sup>3</sup>
<institution>Centre for Sensorimotor Performance, School of Human Movement and Nutrition Sciences, University of Queensland</institution>
,<addr-line>Brisbane, QLD</addr-line>
,<country>Australia</country>
</aff>
<author-notes><fn fn-type="edited-by"><p>Edited by: Florian Röhrbein, Technische Universität München, Germany</p>
</fn>
<fn fn-type="edited-by"><p>Reviewed by: Claudio Castellini, Robotik und Mechatronik Zentrum, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Germany; Giuseppe Carbone, University of Cassino, Italy</p>
</fn>
<corresp content-type="corresp" id="cor1">*Correspondence: Sébastien Mick, <email>sebastien.mick@u-bordeaux.fr</email>
; Aymar de Rugy, <email>aymar.derugy@u-bordeaux.fr</email>
</corresp>
</author-notes>
<pub-date pub-type="epub"><day>25</day>
<month>10</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="collection"><year>2017</year>
</pub-date>
<volume>11</volume>
<elocation-id>55</elocation-id>
<history><date date-type="received"><day>18</day>
<month>5</month>
<year>2017</year>
</date>
<date date-type="accepted"><day>27</day>
<month>9</month>
<year>2017</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2017 Mick, Cattaert, Paclet, Oudeyer and de Rugy.</copyright-statement>
<copyright-year>2017</copyright-year>
<copyright-holder>Mick, Cattaert, Paclet, Oudeyer and de Rugy</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract><p>Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude. With the robotic arm from the open source 3D-printed Poppy Humanoid platform simulating a mobile prosthesis, an experiment was carried out with eighteen able-bodied subjects performing a 3-D target-reaching task using each of the three modes. The subjects were given questionnaires to evaluate the quality of their experience with each mode, providing an assessment of their global usability in the context of the task. According to performance metrics and questionnaire results, velocity control modes were found to perform better than position control mode in terms of accuracy and quality of control as well as user satisfaction and comfort. Subjects also seemed to favor quadratic velocity control over linear (proportional) velocity control, even if these two modes did not clearly distinguish from one another when it comes to performance and usability assessment. These results highlight the need to take into account user experience as one of the key criteria for the design of control modes intended to operate limb prostheses.</p>
</abstract>
<kwd-group><kwd>neuroprosthesis</kwd>
<kwd>arm prosthesis</kwd>
<kwd>robotic arm</kwd>
<kwd>real-time control</kwd>
<kwd>control mode</kwd>
<kwd>usability testing</kwd>
</kwd-group>
<funding-group><award-group><funding-source id="cn01">Université de Bordeaux<named-content content-type="fundref-id">10.13039/501100006251</named-content>
</funding-source>
</award-group>
<award-group><funding-source id="cn02">Centre National de la Recherche Scientifique<named-content content-type="fundref-id">10.13039/501100004794</named-content>
</funding-source>
</award-group>
</funding-group>
<counts><fig-count count="7"></fig-count>
<table-count count="2"></table-count>
<equation-count count="3"></equation-count>
<ref-count count="33"></ref-count>
<page-count count="16"></page-count>
<word-count count="13221"></word-count>
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</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Australie</li>
<li>France</li>
</country>
</list>
<tree><country name="France"><noRegion><name sortKey="Mick, Sebastien" sort="Mick, Sebastien" uniqKey="Mick S" first="Sébastien" last="Mick">Sébastien Mick</name>
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<name sortKey="Cattaert, Daniel" sort="Cattaert, Daniel" uniqKey="Cattaert D" first="Daniel" last="Cattaert">Daniel Cattaert</name>
<name sortKey="De Rugy, Aymar" sort="De Rugy, Aymar" uniqKey="De Rugy A" first="Aymar" last="De Rugy">Aymar De Rugy</name>
<name sortKey="Mick, Sebastien" sort="Mick, Sebastien" uniqKey="Mick S" first="Sébastien" last="Mick">Sébastien Mick</name>
<name sortKey="Oudeyer, Pierre Yves" sort="Oudeyer, Pierre Yves" uniqKey="Oudeyer P" first="Pierre-Yves" last="Oudeyer">Pierre-Yves Oudeyer</name>
<name sortKey="Paclet, Florent" sort="Paclet, Florent" uniqKey="Paclet F" first="Florent" last="Paclet">Florent Paclet</name>
</country>
<country name="Australie"><noRegion><name sortKey="De Rugy, Aymar" sort="De Rugy, Aymar" uniqKey="De Rugy A" first="Aymar" last="De Rugy">Aymar De Rugy</name>
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