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基于牛顿-次梯度非光滑贪婪随机化卡兹马尔兹方法求解线性互补问题的机器人多指抓取力与位移计算

Calculation of Robot Multi-Fingered Grasping Force and Displacement Based on the Newton-Subgradient Non-Smooth Greedy Randomized Kaczmarz Method for Solving Linear Complementarity Problem.

作者信息

Ai Zhiwei, Li Chenliang

机构信息

School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China.

School of Artificial Intelligence, Guilin University of Aerospace Technology, Guilin 541004, China.

出版信息

Sensors (Basel). 2025 Apr 5;25(7):2309. doi: 10.3390/s25072309.

Abstract

The calculation of grasping force and displacement is important for multi-fingered stable grasping and research on slipping damage. By linearizing the friction cone, the robot multi-fingered grasping problem can be represented as a linear complementarity problem (LCP) with a saddle-point coefficient matrix. Because the solution methods for LCP proposed in the field of numerical computation cannot be applied to this problem and the Pivot method can only be used for solving specific grasping problems, the LCP is converted into a non-smooth system of equations for solving it. By combining the Newton method with the subgradient and Kaczmarz methods, a Newton-subgradient non-smooth greedy randomized Kaczmarz (NSNGRK) method is proposed to solve this non-smooth system of equations. The convergence of the proposed method is established. Our numerical experiments indicate its feasibility and effectiveness in solving the grasping force and displacement problems of multi-fingered grasping.

摘要

抓取力和位移的计算对于多指稳定抓取和滑动损伤研究至关重要。通过将摩擦锥线性化,机器人多指抓取问题可表示为具有鞍点系数矩阵的线性互补问题(LCP)。由于数值计算领域提出的LCP求解方法无法应用于此问题,且枢轴法仅适用于解决特定抓取问题,因此将LCP转化为非光滑方程组进行求解。通过将牛顿法与次梯度法和卡兹马尔兹法相结合,提出了一种牛顿-次梯度非光滑贪婪随机化卡兹马尔兹(NSNGRK)方法来求解该非光滑方程组。证明了所提方法的收敛性。我们的数值实验表明了其在解决多指抓取的抓取力和位移问题方面的可行性和有效性。

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