Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm
It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Yanbiao [verfasserIn] Wang, Lin [verfasserIn] Chen, Bo [verfasserIn] Wang, Zesheng [verfasserIn] Sun, Peng [verfasserIn] Zheng, Hang [verfasserIn] Xu, Taotao [verfasserIn] Qin, Songyang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Mechanism and machine theory - Amsterdam [u.a.] : Elsevier Science, 1972, 149 |
|---|---|
| Übergeordnetes Werk: |
volume:149 |
| DOI / URN: |
10.1016/j.mechmachtheory.2020.103792 |
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ELV003846059 |
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| 245 | 1 | 0 | |a Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm |
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| 520 | |a It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. | ||
| 650 | 4 | |a Serial-parallel hybrid | |
| 650 | 4 | |a Humanoid arm | |
| 650 | 4 | |a Dynamic load distribution optimization | |
| 650 | 4 | |a Genetic algorithm | |
| 650 | 4 | |a Component coupling characteristics | |
| 700 | 1 | |a Wang, Lin |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Bo |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Zesheng |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Peng |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Hang |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Taotao |e verfasserin |4 aut | |
| 700 | 1 | |a Qin, Songyang |e verfasserin |4 aut | |
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10.1016/j.mechmachtheory.2020.103792 doi (DE-627)ELV003846059 (ELSEVIER)S0094-114X(20)30013-6 DE-627 ger DE-627 rda eng 620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Li, Yanbiao verfasserin (orcid)0000-0001-9768-0687 aut Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics Wang, Lin verfasserin aut Chen, Bo verfasserin aut Wang, Zesheng verfasserin aut Sun, Peng verfasserin aut Zheng, Hang verfasserin aut Xu, Taotao verfasserin aut Qin, Songyang verfasserin aut Enthalten in Mechanism and machine theory Amsterdam [u.a.] : Elsevier Science, 1972 149 Online-Ressource (DE-627)319950271 (DE-600)2015519-0 (DE-576)259484873 nnns volume:149 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 52.20 Antriebstechnik Getriebelehre 50.32 Dynamik Schwingungslehre Technische Mechanik 50.25 Robotertechnik AR 149 |
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10.1016/j.mechmachtheory.2020.103792 doi (DE-627)ELV003846059 (ELSEVIER)S0094-114X(20)30013-6 DE-627 ger DE-627 rda eng 620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Li, Yanbiao verfasserin (orcid)0000-0001-9768-0687 aut Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics Wang, Lin verfasserin aut Chen, Bo verfasserin aut Wang, Zesheng verfasserin aut Sun, Peng verfasserin aut Zheng, Hang verfasserin aut Xu, Taotao verfasserin aut Qin, Songyang verfasserin aut Enthalten in Mechanism and machine theory Amsterdam [u.a.] : Elsevier Science, 1972 149 Online-Ressource (DE-627)319950271 (DE-600)2015519-0 (DE-576)259484873 nnns volume:149 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 52.20 Antriebstechnik Getriebelehre 50.32 Dynamik Schwingungslehre Technische Mechanik 50.25 Robotertechnik AR 149 |
| allfields_unstemmed |
10.1016/j.mechmachtheory.2020.103792 doi (DE-627)ELV003846059 (ELSEVIER)S0094-114X(20)30013-6 DE-627 ger DE-627 rda eng 620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Li, Yanbiao verfasserin (orcid)0000-0001-9768-0687 aut Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics Wang, Lin verfasserin aut Chen, Bo verfasserin aut Wang, Zesheng verfasserin aut Sun, Peng verfasserin aut Zheng, Hang verfasserin aut Xu, Taotao verfasserin aut Qin, Songyang verfasserin aut Enthalten in Mechanism and machine theory Amsterdam [u.a.] : Elsevier Science, 1972 149 Online-Ressource (DE-627)319950271 (DE-600)2015519-0 (DE-576)259484873 nnns volume:149 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 52.20 Antriebstechnik Getriebelehre 50.32 Dynamik Schwingungslehre Technische Mechanik 50.25 Robotertechnik AR 149 |
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10.1016/j.mechmachtheory.2020.103792 doi (DE-627)ELV003846059 (ELSEVIER)S0094-114X(20)30013-6 DE-627 ger DE-627 rda eng 620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Li, Yanbiao verfasserin (orcid)0000-0001-9768-0687 aut Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics Wang, Lin verfasserin aut Chen, Bo verfasserin aut Wang, Zesheng verfasserin aut Sun, Peng verfasserin aut Zheng, Hang verfasserin aut Xu, Taotao verfasserin aut Qin, Songyang verfasserin aut Enthalten in Mechanism and machine theory Amsterdam [u.a.] : Elsevier Science, 1972 149 Online-Ressource (DE-627)319950271 (DE-600)2015519-0 (DE-576)259484873 nnns volume:149 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 52.20 Antriebstechnik Getriebelehre 50.32 Dynamik Schwingungslehre Technische Mechanik 50.25 Robotertechnik AR 149 |
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10.1016/j.mechmachtheory.2020.103792 doi (DE-627)ELV003846059 (ELSEVIER)S0094-114X(20)30013-6 DE-627 ger DE-627 rda eng 620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Li, Yanbiao verfasserin (orcid)0000-0001-9768-0687 aut Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics Wang, Lin verfasserin aut Chen, Bo verfasserin aut Wang, Zesheng verfasserin aut Sun, Peng verfasserin aut Zheng, Hang verfasserin aut Xu, Taotao verfasserin aut Qin, Songyang verfasserin aut Enthalten in Mechanism and machine theory Amsterdam [u.a.] : Elsevier Science, 1972 149 Online-Ressource (DE-627)319950271 (DE-600)2015519-0 (DE-576)259484873 nnns volume:149 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 52.20 Antriebstechnik Getriebelehre 50.32 Dynamik Schwingungslehre Technische Mechanik 50.25 Robotertechnik AR 149 |
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Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics |
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Li, Yanbiao @@aut@@ Wang, Lin @@aut@@ Chen, Bo @@aut@@ Wang, Zesheng @@aut@@ Sun, Peng @@aut@@ Zheng, Hang @@aut@@ Xu, Taotao @@aut@@ Qin, Songyang @@aut@@ |
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Li, Yanbiao ddc 620 bkl 52.20 bkl 50.32 bkl 50.25 misc Serial-parallel hybrid misc Humanoid arm misc Dynamic load distribution optimization misc Genetic algorithm misc Component coupling characteristics Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm |
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620 DE-600 52.20 bkl 50.32 bkl 50.25 bkl Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm Serial-parallel hybrid Humanoid arm Dynamic load distribution optimization Genetic algorithm Component coupling characteristics |
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ddc 620 bkl 52.20 bkl 50.32 bkl 50.25 misc Serial-parallel hybrid misc Humanoid arm misc Dynamic load distribution optimization misc Genetic algorithm misc Component coupling characteristics |
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optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm |
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Optimization of dynamic load distribution of a serial-parallel hybrid humanoid arm |
| abstract |
It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. |
| abstractGer |
It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. |
| abstract_unstemmed |
It is a big challenge to ensure the low energy consumption and stability of the hybrid mechanism under the dynamic load condition, and it is more obvious in the series-parallel mechanism. In this paper, a 6 degrees-of-freedom (DOF) serial-parallel hybrid humanoid arm by constituting the distribution of “2-1-3” is constructed, and a dynamic load distribution optimization method is studied systematically. The kinematics and dynamics model of the humanoid arm are established by Denavit–Hartenberg (DH) method, Lagrange formulation and the principle of virtual work which can clearly show the coupling characteristics between the components, respectively. Meanwhile, the optimal space point has been attained by a genetic algorithm via the dynamic performance evaluation index and force mapping performance evaluation index are derived based on the dynamic model, and the comprehensive performance evaluation index is defined by the weighted summation method which convert multiple comprehensive performance evaluation model into a single-objective model. Furthermore, the position and posture trajectory of the best performance and the optimal comprehensive objective function are solved by a genetic algorithm, which enables the robot to complete the movement with the lowest energy consumption, the fastest and smoothest way, and the feasibility of this method is verified by numerical example. The work laid a theoretical foundation for the engineering application of the humanoid arm. |
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| score |
7.4009247 |