Fuzzy Neural Network-based Inverse Kinematics Problem of Robotic Manipulators

Abstract

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.