Modeling of robot inverse kinematics using two ANN paradigms

Abstract

The comparison of the performance of two artificial neural network or ANN paradigms trained to learn data obtained from the kinematics model of a UMI RTX robotic arm are presented. Trained ANN simulators were implemented to position the robotic manipulator demonstrating the feasibility of using ANN technology in actual implementation.