DocumentCode
2721309
Title
Calculation of robot parameters based on neural nets
Author
Lesewed, Ali ; Kurek, Jerzy
Author_Institution
Inst. of Autom. Control & Robotics, Warsaw Univ. of Technol., Warszawa, Poland
fYear
2005
fDate
23-25 June 2005
Firstpage
117
Lastpage
122
Abstract
The paper describes applications of recurrent neural network and back propagation learning method for calculation of mathematical model for PUMA 560 robot. The model is based on the Lagrange-Euler formulation and described by a set of nonlinear differential and algebraic equations. A numerical example has shown the comparison of neural model and robot manipulator.
Keywords
backpropagation; linear algebra; manipulator dynamics; nonlinear differential equations; nonlinear systems; recurrent neural nets; uncertain systems; Lagrange-Euler formulation; PUMA 560 robot; algebraic equations; back propagation learning; mathematical model; neural model; neural nets; nonlinear differential equations; recurrent neural network; robot dynamics; robot manipulator; robot parameters; Differential equations; Friction; Lagrangian functions; Manipulator dynamics; Neural networks; Nonlinear equations; Recurrent neural networks; Robot control; Symmetric matrices; Uncertainty; Puma 560 robot; dynamic model; neural nets;
fLanguage
English
Publisher
ieee
Conference_Titel
Robot Motion and Control, 2005. RoMoCo '05. Proceedings of the Fifth International Workshop on
Print_ISBN
83-7143-266-6
Type
conf
DOI
10.1109/ROMOCO.2005.201411
Filename
1554390
Link To Document