基于模糊神经网络的机器人逆运动学问题

Fuzzy Neural Network-based Inverse Kinematics Problem of Robotic Manipulators

模糊神经网络(FNN, Fuzzy Neural Network)结合了神经网络和模糊逻辑的优点,即可以容易的表达模糊定性的知识,又具有较好的学习能力。针对机器人逆运动学问题,本文首次提出了基于模糊神经网络的解决方案,阐述了基本设计思想和具体算法过程,对二自由度刚性机器人的仿真结果表明了该方案的有效性和可行性。

Fuzzy Neural Network(FNN) shows the advantages of both the Neural Network and Fuzzy Logic, which can express the fuzzy and quantilitive knowledge easily and has good learning capability. A method based on FNN is firstly proposed in this paper, which deals with the inverse kinematics problem of Robotic manipulators. The fundamental idea of the FNN and specific algorithm are given. The simulation results are presented for a 2-DOF rigid Robotic manipulators, which validate the effectiveness and feasibility of the proposed scheme.