Neural Network Learning Algorithms for High-Precision Position Control and Drift Attenuation in Robotic Manipulators

Neural Network Learning Algorithms for High-Precision Position Control and Drift Attenuation in Robotic Manipulators

In this paper, different learning methods based on Artificial Neural Networks (ANNs) are examined to replace the default speed controller for high-precision position control and drift attenuation in robotic manipulators. ANN learning methods including Levenberg–Marquardt and Bayesian Regression are...

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Bibliographic Details
Main Authors: Arkadiusz Mystkowski, Adam Wolniakowski, Nesrine Kadri, Mateusz Sewiolo, Lorenzo Scalera
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Applied Sciences
Subjects:
robotics
neural network
learning algorithm
trajectory tracking
UR5 robot
Online Access:https://www.mdpi.com/2076-3417/13/19/10854

Internet

https://www.mdpi.com/2076-3417/13/19/10854

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