Title: An artificial neural network strategy for the forward kinematics of robot control

Authors: Ali T. Hasan, A.M.S. Hamouda, N. Ismail, H.M.A.A. Al-Assadi

Addresses: Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400UPM, Serdang, Selangor, Malaysia. ' Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400UPM, Serdang, Selangor, Malaysia. ' Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400UPM, Serdang, Selangor, Malaysia. ' Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400UPM, Serdang, Selangor, Malaysia

Abstract: This paper is devoted to the development and implementation of the neural network technique to solve the forward kinematics problems of robot control, which are mainly singularities and non-linearities. In this paper, a network has been trained to learn the set of end effecter positions X, Y and Z from a given set of joint angle positions for a 6 D.O.F industrial robot. Training data sets were uniformly distributed over a particular region of the robot|s working area so that the network can make good generalisation for the intermediate points. Experimental results have shown a good mapping over the working area for the robot. The proposed control technique does not require any prior knowledge of the kinematics model of the system to be controlled; the basic idea of this concept is to use a neural network to learn the characteristics of the robot system rather than having to specify explicit robot system model, which is a significant advantage of using neural network technology. Any modifications in the physical set-up of the system would involve only training the robot in a new path without the need for any major software modification.

Keywords: neural networks; forward kinematics; back propagation; robot control; inteligent systems; robot kinematics; robotics.

DOI: 10.1504/IJISTA.2007.011572

International Journal of Intelligent Systems Technologies and Applications, 2007 Vol.2 No.1, pp.41 - 49

Published online: 02 Dec 2006 *

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