A New Technique to Improve Estimation of Position for Serial Robots

This paper presents a new method to improve the estimation of the positions for serial robots using power-activated feed-forward neural network. In the paper, a six-input three-output neural network is created with robot joint angle sine values as inputs and positions in the world frame as outputs. The neuron is activated with an orthogonal polynomial sequence,and the neural weights can be calculated directly without involving iterative and convergent problem. It is found that, the RMS error is less than 0.25 mm for the whole work space. And the absolute and relative errors of this method are smaller than those of built in kinematics model and the traditional back propagation (BP) neural network method. Experimental results show that the proposed method can effectively predict the positioning of the given joint angles.

[1]  Wei Li,et al.  A weights-directly-determined simple neural network for nonlinear system identification , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[2]  William K. Veitschegger,et al.  Robot accuracy analysis based on kinematics , 1986, IEEE J. Robotics Autom..

[3]  Zhu Xiao Lin.  Numerical Analysis , 2014 .

[4]  J. M. Lewis,et al.  A neural network approach to the robot inverse calibration problem , 1994 .

[5]  Chi-haur Wu,et al.  The Kinematic Error Model for the Design of Robot Manipulator , 1983, 1983 American Control Conference.

[6]  Bahram Ravani,et al.  An overview of robot calibration , 1987, IEEE Journal on Robotics and Automation.

[7]  John M. Lewis,et al.  Inverse robot calibration using artificial neural networks , 1996 .

[8]  Henry W. Stone,et al.  Kinematic Modeling, Identification, and Control of Robotic Manipulators , 1987 .

[9]  Jiang Xiaohua,et al.  An algorithm for designing Chebyshev neural network , 2009, 2009 ISECS International Colloquium on Computing, Communication, Control, and Management.

[10]  J. Denavit,et al.  A kinematic notation for lower pair mechanisms based on matrices , 1955 .

[11]  Luo Fei,et al.  An Overview of Robot Calibration , 2004 .

[12]  Samad Hayati,et al.  Robot arm geometric link parameter estimation , 1983, The 22nd IEEE Conference on Decision and Control.

[13]  G. Gatti,et al.  A practical approach to compensate for geometric errors in measuring arms: application to a six-degree-of-freedom kinematic structure , 2007 .