Volume 8, Issue 2 (Journal of Control, V.8, N.2 Summer 2014)                   JoC 2014, 8(2): 11-20 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Nadi F, Derhami V, Rezaeian M. Vision Based Robot Manipulator Control with Neural Modeling of Jacobian Matrix. JoC. 2014; 8 (2) :11-20
URL: http://joc.kntu.ac.ir/article-1-158-en.html
1- Yazd University
Abstract:   (10323 Views)
Visual servoing system is a system to control a robot by visual feedback so that robot drives from any arbitrary start position to the target positions. Various ways, including control by using model of the robot, designing controller directly, and using Jacobian matrix have been studied. Since there is not access to model of robot and obtaining a model of robot would be difficult and time consuming, in many cases, the control law is obtained using Jacobian matrix. In this paper, inverse of Jacobian matrix is approximated using artificial neural networks. The approximated neural models are used in control law directly. For each degree of freedom of the robot manipulator, a two-layer feedforward neural network is considered. The distance between end-effector and target along the x-axis and y-axis, and the shoulder joint coordinates along the x-axis and y-axis are the inputs of each of the networks and the outputs are the fraction of the related robot joint changes to the image features changes (the elements of the inverse of Jacobian matrix). The proposed method has been implemented on a real robot manipulator. The experimental results show that the proposed control system can move the end-effector to different target positions in workspace with good accuracy.
Full-Text [PDF 982 kb]   (3111 Downloads)    
Type of Article: Review paper | Subject: Special
Received: 2014/09/26 | Accepted: 2015/02/1 | Published: 2015/02/1

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 CC BY-NC 4.0 | Journal of Control

Designed & Developed by : Yektaweb