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

机译:基于PSO-RBF网络的PUMA560机械臂逆运动学求解方法

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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.
机译:本文介绍了使用粒子群算法和k最近邻方法优化径向基函数(RBF)网络的过程,并使用Denavit-Hartenberg(DH)方法研究PUMA560机器人,正向运动学的结果是导出为RBF网络训练样本。我们使用十二个输入,单个输出的六个相同的RBF网络来实现PUMA560逆运动学计算。仿真结果表明,该方法具有较高的精度和收敛速度。

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