A QP Artificial Neural Network inverse kinematic solution for accurate robot path control |
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Authors: | ?ahin Y?ld?r?m ?kbal Eski |
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Affiliation: | (1) Faculty of Engineering, Mechanical Engineering Department, Erciyes University, 38039 Kayseri, Turkey |
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Abstract: | In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines,
including robot control, where they can be used to solve nonlinear control problems. One of these ANNs applications is that
of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to
analyse of inverse kinematics of PUMA 560 type robot. The neural network is designed to find exact kinematics of the robot.
The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for
designing exact inverse model of the robot. The Unimation PUMA 560 is a robot with six degrees of freedom and rotational joints.
Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot.
From the simulation results, the proposed neural network has superior performance for modelling complex robot’s kinematics. |
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Keywords: | Artificial Neural Network Robot Path Control PUMA Robot |
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