Inverse Kinematics for Robotic Manipulators via Deep Neural Networks: Experiments and Results

Inverse Kinematics for Robotic Manipulators via Deep Neural Networks: Experiments and Results

This paper explores the application of Deep Neural Networks (DNNs) to solve the Inverse Kinematics (IK) problem in robotic manipulators. The IK problem, crucial for ensuring precision in robotic movements, involves determining joint configurations for a manipulator to reach a desired position or ori...

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Bibliographic Details
Main Authors: Ana Calzada-Garcia, Juan G. Victores, Francisco J. Naranjo-Campos, Carlos Balaguer
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
deep learning
inverse kinematics
robotics
curriculum learning
Online Access:https://www.mdpi.com/2076-3417/15/13/7226
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