A QP artificial neural network inverse kinematic solution for accurate robot path control

作     者：Yildirim, Sahin Eski, Ikbal 

作者机构：Erciyes Univ Fac Engn Mech Engn Dept TR-38039 Kayseri Turkey 

出 版 物：《JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY》 (韩国机械工程师学会国际杂志)

年 卷 期：2006年第20卷第7期

页      面：917-928页

核心收录：

学科分类：08[工学] 0802[工学-机械工程] 

主　　题：Artificial Neural Network robot path control PUMA robot 

摘      要：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.