Work

Block Subgradient Greedy Kaczmarz Methods for Robotic Grasping Problems

Year: 2026

Type: article

Abstract: The robotic grasping problem is firstly cast as a linear complementarity problem and reformulated into nonsmooth equations. We propose two block Kaczmarz methods to solve the equations. The K-means clustering algorithm is utilized to partition the nonsmooth equations. Based on the resulting block information, the subgradient greedy randomized Kaczmarz method and the subgradient multi-step greedy Kaczmarz method are constructed. Asymptotic convergence of the proposed block subgradient Kaczmarz methods is given. Numerical results confirm the superior computational accuracy of the new methods.

Source: Axioms

DOI: 10.3390/axioms15070491

Authors: Zhiwei Ai, Chenliang Li

Institutions: Guilin University of Aerospace Technology, Guilin University of Electronic Technology

Language: English

Topic: Optimization and Variational Analysis

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: National Natural Science Foundation of China