Neural Control for a Differential Drive Wheeled Mobile Robot Integrating Stereo Vision Feedback

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.