Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control
Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was impleme...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Khan, Said Ghani [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science & Business Media BV 2010 |
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| Übergeordnetes Werk: |
Enthalten in: International Journal of Social Robotics - Dordrecht [u.a.] : Springer Netherlands, 2009, 2(2010), 3 vom: 13. Mai, Seite 305-319 |
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| Übergeordnetes Werk: |
volume:2 ; year:2010 ; number:3 ; day:13 ; month:05 ; pages:305-319 |
| Links: |
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| DOI / URN: |
10.1007/s12369-010-0058-7 |
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| Katalog-ID: |
SPR025032879 |
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| 100 | 1 | |a Khan, Said Ghani |e verfasserin |4 aut | |
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| 520 | |a Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. | ||
| 650 | 4 | |a Adaptive compliance control |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Safe human-robot-interaction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Anti-windup compensation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Posture control |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Herrmann, Guido |4 aut | |
| 700 | 1 | |a Pipe, Tony |4 aut | |
| 700 | 1 | |a Melhuish, Chris |4 aut | |
| 700 | 1 | |a Spiers, Adam |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t International Journal of Social Robotics |d Dordrecht [u.a.] : Springer Netherlands, 2009 |g 2(2010), 3 vom: 13. Mai, Seite 305-319 |w (DE-627)595709982 |w (DE-600)2486751-2 |x 1875-4805 |7 nnns |
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10.1007/s12369-010-0058-7 doi (DE-627)SPR025032879 (SPR)s12369-010-0058-7-e DE-627 ger DE-627 rakwb eng Khan, Said Ghani verfasserin aut Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science & Business Media BV 2010 Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 Herrmann, Guido aut Pipe, Tony aut Melhuish, Chris aut Spiers, Adam aut Enthalten in International Journal of Social Robotics Dordrecht [u.a.] : Springer Netherlands, 2009 2(2010), 3 vom: 13. Mai, Seite 305-319 (DE-627)595709982 (DE-600)2486751-2 1875-4805 nnns volume:2 year:2010 number:3 day:13 month:05 pages:305-319 https://dx.doi.org/10.1007/s12369-010-0058-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2010 3 13 05 305-319 |
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10.1007/s12369-010-0058-7 doi (DE-627)SPR025032879 (SPR)s12369-010-0058-7-e DE-627 ger DE-627 rakwb eng Khan, Said Ghani verfasserin aut Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science & Business Media BV 2010 Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 Herrmann, Guido aut Pipe, Tony aut Melhuish, Chris aut Spiers, Adam aut Enthalten in International Journal of Social Robotics Dordrecht [u.a.] : Springer Netherlands, 2009 2(2010), 3 vom: 13. Mai, Seite 305-319 (DE-627)595709982 (DE-600)2486751-2 1875-4805 nnns volume:2 year:2010 number:3 day:13 month:05 pages:305-319 https://dx.doi.org/10.1007/s12369-010-0058-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2010 3 13 05 305-319 |
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10.1007/s12369-010-0058-7 doi (DE-627)SPR025032879 (SPR)s12369-010-0058-7-e DE-627 ger DE-627 rakwb eng Khan, Said Ghani verfasserin aut Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science & Business Media BV 2010 Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 Herrmann, Guido aut Pipe, Tony aut Melhuish, Chris aut Spiers, Adam aut Enthalten in International Journal of Social Robotics Dordrecht [u.a.] : Springer Netherlands, 2009 2(2010), 3 vom: 13. Mai, Seite 305-319 (DE-627)595709982 (DE-600)2486751-2 1875-4805 nnns volume:2 year:2010 number:3 day:13 month:05 pages:305-319 https://dx.doi.org/10.1007/s12369-010-0058-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2010 3 13 05 305-319 |
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10.1007/s12369-010-0058-7 doi (DE-627)SPR025032879 (SPR)s12369-010-0058-7-e DE-627 ger DE-627 rakwb eng Khan, Said Ghani verfasserin aut Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science & Business Media BV 2010 Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 Herrmann, Guido aut Pipe, Tony aut Melhuish, Chris aut Spiers, Adam aut Enthalten in International Journal of Social Robotics Dordrecht [u.a.] : Springer Netherlands, 2009 2(2010), 3 vom: 13. Mai, Seite 305-319 (DE-627)595709982 (DE-600)2486751-2 1875-4805 nnns volume:2 year:2010 number:3 day:13 month:05 pages:305-319 https://dx.doi.org/10.1007/s12369-010-0058-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2010 3 13 05 305-319 |
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10.1007/s12369-010-0058-7 doi (DE-627)SPR025032879 (SPR)s12369-010-0058-7-e DE-627 ger DE-627 rakwb eng Khan, Said Ghani verfasserin aut Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science & Business Media BV 2010 Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 Herrmann, Guido aut Pipe, Tony aut Melhuish, Chris aut Spiers, Adam aut Enthalten in International Journal of Social Robotics Dordrecht [u.a.] : Springer Netherlands, 2009 2(2010), 3 vom: 13. Mai, Seite 305-319 (DE-627)595709982 (DE-600)2486751-2 1875-4805 nnns volume:2 year:2010 number:3 day:13 month:05 pages:305-319 https://dx.doi.org/10.1007/s12369-010-0058-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2010 3 13 05 305-319 |
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| author |
Khan, Said Ghani |
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Khan, Said Ghani misc Adaptive compliance control misc Safe human-robot-interaction misc Anti-windup compensation misc Posture control Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control |
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Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control Adaptive compliance control (dpeaa)DE-He213 Safe human-robot-interaction (dpeaa)DE-He213 Anti-windup compensation (dpeaa)DE-He213 Posture control (dpeaa)DE-He213 |
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safe adaptive compliance control of a humanoid robotic arm with anti-windup compensation and posture control |
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Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control |
| abstract |
Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. © Springer Science & Business Media BV 2010 |
| abstractGer |
Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. © Springer Science & Business Media BV 2010 |
| abstract_unstemmed |
Abstract Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots. An adaptive compliance model reference controller was implemented in real-time on a 4 degrees of freedom (DOF) humanoid robotic arm in Cartesian space. The robot manipulator has been controlled in such a way as to follow the compliant passive behaviour of a reference mass-spring-damper system model subject to an externally sensed force. The redundant DOF were used to control the robot motion in a human-like pattern via minimization of effort, a function of gravity. Associated actuator saturation issues were addressed by incorporating a novel anti-windup (AW) compensator originally developed for a neural network scheme. The controller was simulated for a robotic arm representing the Bristol-Elumotion-Robotic-Torso II (BERT II) and then tested on the real BERT II arm. BERT II has been developed in collaboration by Bristol Robotics Laboratory and Elumotion Ltd. © Springer Science & Business Media BV 2010 |
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Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control |
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https://dx.doi.org/10.1007/s12369-010-0058-7 |
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Herrmann, Guido Pipe, Tony Melhuish, Chris Spiers, Adam |
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10.1007/s12369-010-0058-7 |
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2024-07-03T13:28:01.448Z |
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