DocumentCode :
2639844
Title :
Inverse kinematics identification of a spherical robot based on BP neural networks
Author :
Cai, Yao ; Zhan, Qiang ; Xi, Xi ; Rahmani, Ahmed
Author_Institution :
Robot. Inst., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
fYear :
2011
fDate :
21-23 June 2011
Firstpage :
2114
Lastpage :
2119
Abstract :
This paper proposed a method of neural networks to deal with the identification of the inverse kinematics of a spherical robot BHQ-1. The proposed method solves the problems of model error introduced by the generalized inverse method. It can compensate the external perturbation in the actual environment by applying an on-line learning technique, which improves the precision of the inverse kinematics model. Neural networks can approximate arbitrary order nonlinear systems and the robustness of neural networks has been proved, which shows that the deduced inverse system can be applied to actual control of spherical robot. At last, some test data has been used to validate the performance of the off-line trained model and the simulation results show that the inverse model is accurate and stable.
Keywords :
backpropagation; learning (artificial intelligence); mobile robots; neural nets; nonlinear control systems; robot kinematics; BHQ-1; BP neural networks; arbitrary order nonlinear systems; deduced inverse system; generalized inverse method; inverse kinematics identification; offline trained model; online learning technique; spherical robot; Artificial neural networks; Inverse problems; Kinematics; Mathematical model; Robot kinematics; Training; inverse kinematics; neural networks identification; spherical robot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
Conference_Location :
Beijing
ISSN :
pending
Print_ISBN :
978-1-4244-8754-7
Electronic_ISBN :
pending
Type :
conf
DOI :
10.1109/ICIEA.2011.5975941
Filename :
5975941
Link To Document :
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