基于BP神经网络5 P4R并联机构位置正解研究

并联机器人机构位置正解问题是机器人机构的应用基础也是运动学研究中的难点之一。针对数值法和解析法的复杂和求解难度以及有时求解的不唯一性,提出了一种多层前向神经网络求解3自由度5-P4R并联机构位置正解的方法。将位置反解作为训练样本,采用学习率可变的BP算法,实现了从驱动工作空间到动平台变量空间的非线性映射,从而得到并联机构运动学正解值。最后给出一组仿真实例,可以看出此方法的有效性与可行性。

Study on Solution for Forward Kinematics of 5 P4R Parallel Mechanism Based on BP Neural Network

The forward kinematics solution for problem of parallel robot mechanism is the basis of application of robot mechanism , and it is one of the difficulties in the study of kinematics .Aimed at the numerical method and analytical method of the complex and sol-ving difficulty and sometimes the uncertainty in solution , it was put forward the method of multilayer feed forward neural network for solving the forward kinematics of three degree of freedom (3-DOF) 5-P4R parallel mechanism .The inverse kinematics solution was re-gard as the trained sample , and the vector variable in study of BP algorithm was used , and then the nonlinear mapping from driver workspace to the moving platform variable space was achieved , so the parallel mechanism forward kinematics solution was obtained .At last, a set of simulation instance is given .It can be seen that the validity and feasibility of this method .