Joint friction estimation for walking bipeds
This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact...
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| Veröffentlicht in: | Robotica 2016-07, Vol.34 (7), p.1610-1629 |
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| container_title | Robotica |
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| creator | Hashlamon, Iyad Erbatur, Kemalettin |
| description | This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach. |
| doi_str_mv | 10.1017/S0263574714002471 |
| format | Article |
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The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.</description><identifier>ISSN: 0263-5747</identifier><identifier>EISSN: 1469-8668</identifier><identifier>DOI: 10.1017/S0263574714002471</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Contact ; Estimates ; Friction ; Grounds ; Mathematical models ; Robots ; Strategy ; Walking</subject><ispartof>Robotica, 2016-07, Vol.34 (7), p.1610-1629</ispartof><rights>Copyright © Cambridge University Press 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c350t-e4d4bd092bb31e57b059247dc0b9f009a556ada97a575b618c1cc292d2df2c5b3</citedby><cites>FETCH-LOGICAL-c350t-e4d4bd092bb31e57b059247dc0b9f009a556ada97a575b618c1cc292d2df2c5b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S0263574714002471/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,315,781,785,27929,27930,55633</link.rule.ids></links><search><creatorcontrib>Hashlamon, Iyad</creatorcontrib><creatorcontrib>Erbatur, Kemalettin</creatorcontrib><title>Joint friction estimation for walking bipeds</title><title>Robotica</title><addtitle>Robotica</addtitle><description>This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.</description><subject>Contact</subject><subject>Estimates</subject><subject>Friction</subject><subject>Grounds</subject><subject>Mathematical models</subject><subject>Robots</subject><subject>Strategy</subject><subject>Walking</subject><issn>0263-5747</issn><issn>1469-8668</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1UE1LxDAUDKLguvoDvBW8eLD6Xto0zVEWP1nwoJ5Lvrpk7TZr0kX896buHkTxNA_ezDAzhJwiXCIgv3oGWhWMlxxLAJpgj0ywrEReV1W9TybjOx__h-QoxiUAFljyCbl49K4fsjY4PTjfZzYObiW_z9aH7EN2b65fZMqtrYnH5KCVXbQnO5yS19ubl9l9Pn-6e5hdz3NdMBhyW5pSGRBUqQIt4wqYSJGMBiVaACEZq6SRgkvGmaqw1qg1FdRQ01LNVDEl51vfdfDvmxSpWbmobdfJ3vpNbLCmLHWrkCbq2S_q0m9Cn9I1yAVlwDmMLNyydPAxBts265Bqhs8GoRn3a_7slzTFTiNXKjizsD-s_1V9AQkAcBk</recordid><startdate>201607</startdate><enddate>201607</enddate><creator>Hashlamon, Iyad</creator><creator>Erbatur, Kemalettin</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>201607</creationdate><title>Joint friction estimation for walking bipeds</title><author>Hashlamon, Iyad ; Erbatur, Kemalettin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c350t-e4d4bd092bb31e57b059247dc0b9f009a556ada97a575b618c1cc292d2df2c5b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Contact</topic><topic>Estimates</topic><topic>Friction</topic><topic>Grounds</topic><topic>Mathematical models</topic><topic>Robots</topic><topic>Strategy</topic><topic>Walking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hashlamon, Iyad</creatorcontrib><creatorcontrib>Erbatur, Kemalettin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Proquest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Robotica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hashlamon, Iyad</au><au>Erbatur, Kemalettin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Joint friction estimation for walking bipeds</atitle><jtitle>Robotica</jtitle><addtitle>Robotica</addtitle><date>2016-07</date><risdate>2016</risdate><volume>34</volume><issue>7</issue><spage>1610</spage><epage>1629</epage><pages>1610-1629</pages><issn>0263-5747</issn><eissn>1469-8668</eissn><abstract>This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/S0263574714002471</doi><tpages>20</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0263-5747 |
| ispartof | Robotica, 2016-07, Vol.34 (7), p.1610-1629 |
| issn | 0263-5747 1469-8668 |
| language | eng |
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| source | Cambridge University Press Journals Complete |
| subjects | Contact Estimates Friction Grounds Mathematical models Robots Strategy Walking |
| title | Joint friction estimation for walking bipeds |
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