Neural Control for a Differential Drive Wheeled Mobile Robot Integrating Stereo Vision Feedback
Michel López-Franco1, Edgar N. Sánchez1, Alma Y. Alanis2, Carlos López-Franco2
1 Instituto Politécnico Nacional, CINVESTAV, Unidad Guadalajara, Jalisco, México. mlopez@gdl.cinvestav.mx, sanchez@gdl.cinvestav.mx
2 Universidad de Guadalajara, CUCEI, Jalisco, México. almayalanis@gmail.com, carlos.lopez@cucei.udg.mx
Corresponding author is Michel López-Franco.
]]> Article received on 24/11/2014.
Abstract
This paper proposes a tracking control method for a differential drive wheeled mobile robot with nonholonomic constraints with an inverse optimal neural controller. It is based on two techniques: first, an identifier using a discrete-time recurrent high-order neural network (RHONN) trained with an extended Kalman filter (EKF) algorithm is employed; second, an inverse optimal control is used to avoid solving the Hamilton Jacobi Bellman (HJB) equation. The desired trajectory of the robot is computed during the navigation process using a stereo camera sensor.
Keywords: Neural control, tracking control, differential drive steering, identifier, inverse optimal control.
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Acknowledgements
]]> The authors thank CONACYT, Mexico, for the support through Projects 103191Y, 156567Y, and INFR- 229696.
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