关键词: 径向基函数, 神经网络, 运动学正解, 并联机器人, 最近邻聚类法

Abstract: The kinematic model of parallel manipulators presents an inherent complexity due to their closed-loop structure and kinematic constraints and, correspondingly, the algorithm for the solution to relevant direct kinematic problems is complex. An algorithm of RBFNN for kinematic problems is thus presented in a nearest neighbor-clustering way to solve simply the positions and orientations of Stewart platform with needed precision, of which the process of solution is simple with good result provided. Comparing with the Newton-Raphson algorithm, the errors of neural network are approximatively invariable without the effects of initial values and rated number of cycles on them. The results show that this approach can be used for the in-line control of parallel manipulators.