The traditional solutions to the inverse kinematics of the robot is very complicated because of the need of a large number of formula derivation. And,the new neural network-based algorithms always have some limitations and shortcomings,therefore,in this paper,it devotes to find a simple and fast method of sol-ving inverse kinematics based on the analysis of the existing neural network models. So, considering the out-standing performance of RBF neural network in nonlinear function approximation, this paper puts out a par-allel neural networks modal which have two RBF neural network with the same structure. Taking NACHI-MZ04 robot as an example, modeling of kinematics at first , it manipulates the necessary data for training and testing the neural networks , then based on neural network toolbox, it builds the network model which it trains and tests after setting it up, and finally it meets the precision requirement of network model. It shows that the method applied to the solution of the inverse kinematics has good application results and is worth u-sing widely.%机器人逆运动求解的传统方法因为需要大量公式推导往往繁琐复杂,新出现的基于神经网络的算法又存在一定的局限和不足,所以,文章在分析现有神经网络模型的基础上致力于找到一种简单快速的求解方法.考虑到RBF神经网络在非线性函数逼近中的优秀表现,文章将两个相同结构的RBF神经网络应用于机器人逆运动求解中.以NACHI-MZ04型机器人为例,首先建立其运动学模型并在此基础上得到用以训练和测试神经网络的数据,然后基于Matlab nntool搭建网络模型并分别对网络进行训练和测试,最后得到满足精度要求的网络模型.结果表明,该方法在逆运动求解问题中应用效果良好,具有一定的推广价值.
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