Proceedings ArticleDOI
A real-time approach using feed forward neural network for a 5 DOF robot manipulator
TLDR
The Conclusive simulation shows that, by utilizing this new calculating algorithm, it can give a precise inverse kinematics solution quick and has higher efficiency.Abstract:
This paper displays a procedure for solving the inverse kinematics problem utilizing neural networks in realtime application. The inverse kinematics problem for a robotic manipulator is acquired for the required manipulator joint values for a given desired end point position and orientation. The proposed strategy yields various and exact arrangements and it is suitable for real-time applications. The Conclusive simulation shows that, by utilizing this new calculating algorithm, it can give a precise inverse kinematics solution quick and has higher efficiency. Aside from these, when utilizing as a part of practice, it additionally mirrors a flawless execution.read more
Citations
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Journal ArticleDOI
Voice Recognition and Inverse Kinematics Control for a Redundant Manipulator Based on a Multilayer Artificial Intelligence Network
Mai Ngoc Anh,Duong Xuan Bien +1 more
TL;DR: The construction of a Vietnamese voice recognition module and inverse kinematics control of a redundant manipulator by using artificial intelligence algorithms and the efficient operation of the built deep learning networks demonstrates the reliability of the artificial intelligence algorithm and the applicability of the Vietnamese voice Recognition module for various tasks.
References
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Theory and applications of neural networks for industrial control systems
Toshio Fukuda,Takanori Shibata +1 more
TL;DR: The theory and the applications of artificial neural networks, especially in a control field, are described and recurrent networks and feedforward networks are discussed.
Journal ArticleDOI
A dual neural network for kinematic control of redundant robot manipulators
Youshen Xia,Jun Wang +1 more
TL;DR: The dual network is presented, which is composed of a single layer of neurons, and the number of neurons is equal to the dimensionality of the workspace, and is proven to be globally exponentially stable.
Journal ArticleDOI
Inverse kinematics in robotics using neural networks
TL;DR: A solution based on structured neural networks that can be trained quickly and suitable for real-time applications is proposed for the inverse kinematics problem in robotics.
Journal ArticleDOI
A neural network based feedforward adaptive controller for robots
TL;DR: An adaptive controller for robot manipulators which uses neural networks is presented, based on PD feedback plus a feedforward compensation of full robot dynamics and stability analysis which takes into account neural network learning errors.
Proceedings ArticleDOI
Comparison of inverse kinematics solutions using neural network for 6R robot manipulator with offset
TL;DR: In this paper, an ANN using backpropagation algorithm is applied to solve inverse kinematics problems of industrial robot manipulator 6R robot with offset wrist, which is a robot with an offset wrist.