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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 22 | Page No.: 3957-3965
DOI: 10.3923/jas.2009.3957.3965
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State Estimation for Mobile Robot Using Neural Networks

S. Chouraqui and M. Benyettou

In this study, we describe a state estimation method using neural networks. The developed method has been applied to the problem of estimating the parameter of a six degree of freedom (DOF) PUMA 560 Robot arm manipulator. The results obtained were compared with the conventional Extended Kalman Filter, showing an improvement in performance and robustness. From the simulations performed, it can be said that the neural filter proposed for the studied application is more consisted and convergent than the EKF filter.
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How to cite this article:

S. Chouraqui and M. Benyettou, 2009. State Estimation for Mobile Robot Using Neural Networks. Journal of Applied Sciences, 9: 3957-3965.

DOI: 10.3923/jas.2009.3957.3965






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