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

Author

Li, Zhe Ming ; Li, Chun Gui ; Lv, Shao Jiao

Author_Institution

Dept. of Electron. Inf. & Control Eng., Guangxi Univ. of Technol., Liuzhou, China

fYear

2012

fDate

29-31 May 2012

Firstpage

298

Lastpage

301

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.

Keywords

manipulator kinematics; particle swarm optimisation; pattern clustering; radial basis function networks; DH method; Denavit-Hartenberg method; PSO-RBF network; PUMA560 manipulator inverse kinematics; RBF network training samples; forward kinematics; k-nearest neighbor method; particle swarm algorithm; radial basis function network; Artificial neural networks; Joints; Kinematics; Radial basis function networks; Robot kinematics; Vectors; Inverse kinematicss; PUMA560 robot; k-nearest neighbor method; particle swarm algorithm; radial basis function network;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2012 Eighth International Conference on

Conference_Location

Chongqing

ISSN

2157-9555

Print_ISBN

978-1-4577-2130-4

Type

conf

DOI

10.1109/ICNC.2012.6234507

Filename

6234507