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KINEMATICS ANALYSIS AND NUMERICAL SIMULATION OF HYBRID SERIAL-PARALLEL MANIPULATOR BASED ON NEURAL NETWORK

机译:基于神经网络的混合串并联机械手运动学分析与数值模拟

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摘要

This paper presents solution of kinematics analysis of a specific class of serial-parallel manipulators, known as 2-(6UPS) manipulators, which are composed of several modules consisting of elementary manipulators with the parallel structure of the Stewart platform, by artificial neural network. At first, the kinematics model of the hybrid manipulator is obtained. Then, as the inverse kinematics problem of this kind of manipulators is a very difficult problem to solve because of their highly nonlinear relations between joint variables and position and orientation of the end effectors, a wavelet based neural network (wave-net) with its inherent learning ability as a strong method was used to solve the inverse kinematics problem. Also, the proposed wavelet neural network (WNN) is applied to approximate the paths of middle and upper plate in a circular and a spiral path, respectively. The results show high accurate performance of the proposed WNN.
机译:本文提出了一种特定类型的串行并行机械手的运动学分析解决方案,称为2-(6UPS)机械手,该机械手由数个模块组成,这些模块由基本机械手组成,这些机械手与Stewart平台具有并行结构,是通过人工神经网络实现的。首先,获得了混合机械手的运动学模型。然后,由于这种机械手的逆运动学问题是一个非常难解决的问题,因为它们的关节变量与末端执行器的位置和方向之间存在高度非线性关系,因此基于小波的神经网络(wave-net)具有固有的学习能力作为一种强大的方法被用来解决运动学逆问题。此外,提出的小波神经网络(WNN)分别用于近似圆形和螺旋形路径中的中板和上板的路径。结果表明所提出的WNN具有很高的准确度。

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