Force control for position interface industrial manipulator working in unknown environment

Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industri...
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Gespeichert in:

Autor*in:	Al Mashagbeh, Mohammad [verfasserIn] Khamesee, Mir Behrad [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Contact Force Force Control Admittance Control Fuzzy Logic Controller Fuzzy Logic Control

Übergeordnetes Werk:	Enthalten in: Microsystem technologies - Berlin : Springer, 1994, 21(2015), 12 vom: 26. März, Seite 2557-2563
Übergeordnetes Werk:	volume:21 ; year:2015 ; number:12 ; day:26 ; month:03 ; pages:2557-2563

Links:	Volltext

DOI / URN:	10.1007/s00542-015-2492-9

Katalog-ID:	SPR006832253

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520			\|a Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N.
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matchkey_str	article:14321858:2015----::occnrlopstoitraenutilaiuaowrig
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allfields	10.1007/s00542-015-2492-9 doi (DE-627)SPR006832253 (SPR)s00542-015-2492-9-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Al Mashagbeh, Mohammad verfasserin aut Force control for position interface industrial manipulator working in unknown environment 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N. Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213 Khamesee, Mir Behrad verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2015), 12 vom: 26. März, Seite 2557-2563 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563 https://dx.doi.org/10.1007/s00542-015-2492-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_152 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_266 GBV_ILN_267 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 50.94 ASE AR 21 2015 12 26 03 2557-2563
spelling	10.1007/s00542-015-2492-9 doi (DE-627)SPR006832253 (SPR)s00542-015-2492-9-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Al Mashagbeh, Mohammad verfasserin aut Force control for position interface industrial manipulator working in unknown environment 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N. Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213 Khamesee, Mir Behrad verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2015), 12 vom: 26. März, Seite 2557-2563 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563 https://dx.doi.org/10.1007/s00542-015-2492-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_152 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_266 GBV_ILN_267 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 50.94 ASE AR 21 2015 12 26 03 2557-2563
allfields_unstemmed	10.1007/s00542-015-2492-9 doi (DE-627)SPR006832253 (SPR)s00542-015-2492-9-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Al Mashagbeh, Mohammad verfasserin aut Force control for position interface industrial manipulator working in unknown environment 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N. Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213 Khamesee, Mir Behrad verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2015), 12 vom: 26. März, Seite 2557-2563 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563 https://dx.doi.org/10.1007/s00542-015-2492-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_152 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_266 GBV_ILN_267 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 50.94 ASE AR 21 2015 12 26 03 2557-2563
allfieldsGer	10.1007/s00542-015-2492-9 doi (DE-627)SPR006832253 (SPR)s00542-015-2492-9-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Al Mashagbeh, Mohammad verfasserin aut Force control for position interface industrial manipulator working in unknown environment 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N. Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213 Khamesee, Mir Behrad verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2015), 12 vom: 26. März, Seite 2557-2563 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563 https://dx.doi.org/10.1007/s00542-015-2492-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_152 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_266 GBV_ILN_267 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 50.94 ASE AR 21 2015 12 26 03 2557-2563
allfieldsSound	10.1007/s00542-015-2492-9 doi (DE-627)SPR006832253 (SPR)s00542-015-2492-9-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Al Mashagbeh, Mohammad verfasserin aut Force control for position interface industrial manipulator working in unknown environment 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N. Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213 Khamesee, Mir Behrad verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2015), 12 vom: 26. März, Seite 2557-2563 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563 https://dx.doi.org/10.1007/s00542-015-2492-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_152 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_266 GBV_ILN_267 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 50.94 ASE AR 21 2015 12 26 03 2557-2563
language	English
source	Enthalten in Microsystem technologies 21(2015), 12 vom: 26. März, Seite 2557-2563 volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563
sourceStr	Enthalten in Microsystem technologies 21(2015), 12 vom: 26. März, Seite 2557-2563 volume:21 year:2015 number:12 day:26 month:03 pages:2557-2563
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institution	findex.gbv.de
topic_facet	Contact Force Force Control Admittance Control Fuzzy Logic Controller Fuzzy Logic Control
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authorswithroles_txt_mv	Al Mashagbeh, Mohammad @@aut@@ Khamesee, Mir Behrad @@aut@@
publishDateDaySort_date	2015-03-26T00:00:00Z
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author	Al Mashagbeh, Mohammad
spellingShingle	Al Mashagbeh, Mohammad ddc 510 bkl 50.94 misc Contact Force misc Force Control misc Admittance Control misc Fuzzy Logic Controller misc Fuzzy Logic Control Force control for position interface industrial manipulator working in unknown environment
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topic_title	510 ASE 50.94 bkl Force control for position interface industrial manipulator working in unknown environment Contact Force (dpeaa)DE-He213 Force Control (dpeaa)DE-He213 Admittance Control (dpeaa)DE-He213 Fuzzy Logic Controller (dpeaa)DE-He213 Fuzzy Logic Control (dpeaa)DE-He213
topic	ddc 510 bkl 50.94 misc Contact Force misc Force Control misc Admittance Control misc Fuzzy Logic Controller misc Fuzzy Logic Control
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title_sort	force control for position interface industrial manipulator working in unknown environment
title_auth	Force control for position interface industrial manipulator working in unknown environment
abstract	Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N.
abstractGer	Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N.
abstract_unstemmed	Abstract Industrial manipulators have multidisciplinary applications. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, high speed motions and a high level of performance. Most industrial manipulators are position controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore in order to use industrial manipulators for delicate tasks, the addition of force and vision sensing mechanisms is required to successfully automate these tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. In this paper, an optical tracking device and a force torque sensor were integrated into a position controlled industrial manipulator to operate in unknown inclined planes. In addition, two types of controllers are presented to control the interaction force. The control techniques are admittance control and fuzzy logic control. The results show the capability of the presented controllers to successfully monitor the interaction force while tracking the position of a passive marker moved by a human operator. The force error using the admittance controller is found to be in the range of ±0.75 N. The fuzzy logic controller on the other hand produces less overshoot relative to the admittance controller, but a higher error of ±1.5 N.
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container_issue	12
title_short	Force control for position interface industrial manipulator working in unknown environment
url	https://dx.doi.org/10.1007/s00542-015-2492-9
remote_bool	true
author2	Khamesee, Mir Behrad
author2Str	Khamesee, Mir Behrad
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doi_str	10.1007/s00542-015-2492-9
up_date	2024-07-04T00:52:31.551Z
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Force control for position interface industrial manipulator working in unknown environment

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