A method for solving inverse kinematics of PUMA560 manipulator based on PSO-RBF network

Zhe Ming Li, Chun Gui Li, S. Lv
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引用次数: 11

Abstract

This paper describes the use of particle swarm algorithm and k-nearest neighbor method to optimize the process of radial basis function (RBF) network and we use the Denavit-Hartenberg (DH) method to research PUMA560 robotics, the results of the forward kinematics is derived as the RBF network training samples. We use six identical RBF network of twelve-input, single output, to achieve a PUMA560 inverse kinematics calculation. Simulation results show that the results obtained with this method has high accuracy and fast convergence.
基于PSO-RBF网络的PUMA560机械手运动学逆解方法
本文介绍了利用粒子群算法和k近邻法对径向基函数(RBF)网络的过程进行优化,并利用Denavit-Hartenberg (DH)方法对PUMA560机器人进行了研究,得到的正运动学结果作为RBF网络的训练样本。采用6个相同的12输入、单输出RBF网络,实现PUMA560的逆运动学计算。仿真结果表明,该方法具有精度高、收敛速度快的特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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