Grasping Force Optimization for Multi-fingered Robotic Hands Using Projection and Contraction Methods
Grasping force optimization of multi-fingered robotic hands can be formulated as a convex quadratic circular cone programming problem, which consists in minimizing a convex quadratic objective function subject to the friction cone constraints and balance constraints of external force. This paper pre...
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| Published in | Journal of optimization theory and applications Vol. 183; no. 2; pp. 592 - 608 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.11.2019
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0022-3239 1573-2878 |
| DOI | 10.1007/s10957-019-01540-9 |
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| Abstract | Grasping force optimization of multi-fingered robotic hands can be formulated as a convex quadratic circular cone programming problem, which consists in minimizing a convex quadratic objective function subject to the friction cone constraints and balance constraints of external force. This paper presents projection and contraction methods for grasping force optimization problems. The proposed projection and contraction methods are shown to be globally convergent to the optimal grasping force. The global convergence makes projection and contraction methods well suited to the warm-start techniques. The numerical examples show that the projection and contraction methods with warm-start version are fast and efficient. |
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| AbstractList | Grasping force optimization of multi-fingered robotic hands can be formulated as a convex quadratic circular cone programming problem, which consists in minimizing a convex quadratic objective function subject to the friction cone constraints and balance constraints of external force. This paper presents projection and contraction methods for grasping force optimization problems. The proposed projection and contraction methods are shown to be globally convergent to the optimal grasping force. The global convergence makes projection and contraction methods well suited to the warm-start techniques. The numerical examples show that the projection and contraction methods with warm-start version are fast and efficient. |
| Author | Zhang, Yaling Mu, Xuewen |
| Author_xml | – sequence: 1 givenname: Xuewen orcidid: 0000-0001-8491-1511 surname: Mu fullname: Mu, Xuewen email: xwmu@xidian.edu.cn organization: School of Mathematics and Statistics, Xidian University – sequence: 2 givenname: Yaling surname: Zhang fullname: Zhang, Yaling organization: School of Mathematics and Statistics, Xidian University, School of Computer Science, Xi’an Science and Technology University |
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| CitedBy_id | crossref_primary_10_1016_j_procs_2022_10_086 crossref_primary_10_1186_s13660_023_02938_w crossref_primary_10_1007_s12206_024_0730_8 crossref_primary_10_1007_s13042_021_01360_2 crossref_primary_10_3390_app132312575 crossref_primary_10_3390_app13179603 |
| Cites_doi | 10.1177/027836499801700802 10.1109/70.744611 10.1080/10556789908805766 10.1109/70.34763 10.3934/naco.2014.4.59 10.1109/TRO.2007.910774 10.1109/70.897778 10.4208/jcm.2009.27.4.013 10.1109/TRA.2002.999643 10.1155/2013/681710 10.1007/BF01581141 10.1287/moor.19.1.53 10.1137/060657662 10.1109/70.54733 10.1137/1.9781611971446 10.1016/S0024-3795(98)10032-0 10.1007/s40305-017-0152-8 10.1007/s11228-008-0092-x |
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| SubjectTerms | Applications of Mathematics Calculus of Variations and Optimal Control; Optimization Circular cones Convergence End effectors Engineering Grasping (robotics) Grasping force Hand (anatomy) Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Projection Regular Paper Theory of Computation |
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| Title | Grasping Force Optimization for Multi-fingered Robotic Hands Using Projection and Contraction Methods |
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