Open AccessInverse Kinematic Solution of 5R Manipulator using ANN and ANFIS
Author(s) -
Panchanand Jha
Publication year - 2015
Publication title -
international journal of robotics and automation (ijra)/iaes international journal of robotics and automation
Language(s) - English
Resource type - Journals
eISSN - 2722-2586
pISSN - 2089-4856
DOI - 10.11591/ijra.v4i2.pp109-123
Subject(s) - adaptive neuro fuzzy inference system , artificial neural network , inverse kinematics , gradient descent , kinematics , neuro fuzzy , computer science , control theory (sociology) , artificial intelligence , multilayer perceptron , robot , fuzzy logic , fuzzy control system , physics , control (management) , classical mechanics
Inverse kinematics of manipulator comprises the computation required to find the joint angles for a given Cartesian position and orientation of the end effector. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Artificial neural network and adaptive neural fuzzy inference system techniques can be gainfully used to yield the desired results. This paper proposes structured artificial neural network (ANN) model and adaptive neural fuzzy inference system (ANFIS) to find the inverse kinematics solution of robot manipulator. The ANN model used is a multi-layered perceptron Neural Network (MLPNN). Wherein, gradient descent type of learning rules is applied. An attempt has been made to find the best ANN configuration for the problem. It is found that ANFIS gives better result and minimum error as compared to ANN.