基于神经网络的并联3自由度机器人位置正解

并联机器人位置正解是机器人运动学中难点问题之一，常规求解方法比较复杂且难度较大，通常需要对大量的非线性方程组进行推导计算且得到的解不唯一。该文提出了一种将人工神经网络用于并联机器人位置正解求解的通用方法，并结合实际机构对并联3自由度机器人进行了具体求解。通过对神经网络拓扑结构的设计以及选取有效的学习算法并用大量的位置反解数据对神经网络进行训练，获得了用于求解位置正解的神经网络模型，该网络可以实现位置正解问题的求解计算，从而避免了复杂的推导和演算。计算机仿真与实验结果表明了该方法的有效性与可行性。

Solution for Forward Kinematics of 3-DOF-Parallel-Robot Based on Neural Network

The kinematics solution of parallel robot is researched by many researchers.The FK(forward kinematics) attracts the interests of many researchers.Using the common method involves the solving of a series of simultaneous non-linear equations and,usually,non-unique,multiple sets of solutions are obtained from one set of data.Here a method based on Nerual Network is presented,a network is constructed and trained by BP algorithm. The proposed method is used to sovle the 3-Dof parallel robot and satisfactory results are obtained.It proves that the method is feasible and effective.