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A Primal-Dual Interior-Point Method for Optimal Grasping Manipulation of Multi-fingered Hand-Arm Robots

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Abstract

In this paper, we consider an optimization problem of the grasping manipulation of multi-fingered hand-arm robots. We first formulate an optimization model for the problem, based on the dynamic equations of the object and the friction constraints. Then, we reformulate the model as a convex quadratic programming over circular cones. Moreover, we propose a primal-dual interior-point algorithm based on the kernel function to solve this convex quadratic programming over circular cones. We derive both the convergence of the algorithm and the iteration bounds for large- and small-update methods, respectively. Finally, we carry out the numerical tests of \(180^{\circ }\) and \(90^{\circ }\) manipulations of the hand-arm robot to demonstrate the effectiveness of the proposed algorithm.

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Authors and Affiliations

  1. Department of Mathematics, Shanghai University, Shanghai, 200444, China

    Yan-Qin Bai, Xue-Rui Gao & Chang-Jun Yu

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  1. Yan-Qin Bai
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  2. Xue-Rui Gao
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  3. Chang-Jun Yu
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Corresponding author

Correspondence to Yan-Qin Bai.

Additional information

This paper is dedicated to Professor Lian-Sheng Zhang in celebration of his 80th birthday.

This research was supported by the National Natural Science Foundation of China (No. 11371242).

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Bai, YQ., Gao, XR. & Yu, CJ. A Primal-Dual Interior-Point Method for Optimal Grasping Manipulation of Multi-fingered Hand-Arm Robots. J. Oper. Res. Soc. China 5, 177–192 (2017). https://doi.org/10.1007/s40305-017-0161-7

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  • DOI: https://doi.org/10.1007/s40305-017-0161-7

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