Investigating Feed-Forward Back-Propagation Neural Network with Different Hyperparameters for Inverse Kinematics of a 2-DoF Robotic Manipulator: A Comparative Study

Investigating Feed-Forward Back-Propagation Neural Network with Different Hyperparameters for Inverse Kinematics of a 2-DoF Robotic Manipulator: A Comparative Study

Inverse kinematics is a significant challenge in robotic manipulators, and finding practical solutions plays a crucial role in achieving precise control. This paper presents a study on solving inverse kinematics problems using the Feed-Forward Back-Propagation Neural Network (FFBP-NN) and examines i...

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Bibliographic Details
Main Authors: Rania Bouzid, Jyotindra Narayan, Hassène Gritli
Format: Article
Language:English
Published: Akif AKGUL 2024-06-01
Series:Chaos Theory and Applications
Subjects:
robotic manipulator
inverse kinematics
feed-forward backpropagation
artifical neural network
hyperparameters
levenberg-marquardt algorithm
bayesian regularization algorithm
scaled conjugate gradient algorithm
different datasets
mean squared error
r-value
Online Access:https://dergipark.org.tr/en/download/article-file/3474279
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