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Grasping Force Optimization for Multi-fingered Robotic Hands Using Projection and Contraction Methods

  • Xuewen MuEmail author
  • Yaling Zhang
Regular Paper
  • 26 Downloads

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.

Keywords

Circular cone programming Second-order cone programming Projection and contraction method SeDuMi software 

Mathematics Subject Classification

90C90 90C25 65K05 

Notes

Acknowledgements

We would like to thank the editor and the anonymous reviewers for their constructive comments, and we benefit much from the suggestions. This work was supported by the National Science Foundations for Young Scientists of China (11101320), the National Science Basic Research Plan in Shaanxi Province of China (2015JM1031), and the Fundamental Research Funds for the Central Universities (JB150713).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsXidian UniversityXi’anChina
  2. 2.School of Computer ScienceXi’an Science and Technology UniversityXi’anChina

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