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

Zhe Ming Li, Chun Gui Li, Shao Jiao Lv

发表年份
2012
引用次数
11

摘要

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.

关键词

Inverse kinematicsParticle swarm optimizationRadial basis functionHierarchical RBFKinematicsConvergence (economics)Artificial neural networkComputer scienceInverseArtificial intelligence

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