Real-Time Inverse Optimal Neural Control for Image Based Visual Servoing with Nonholonomic Mobile Robots

الملخص EN

We present an inverse optimal neural controller for a nonholonomic mobile robot with parameter uncertainties and unknown external disturbances.

The neural controller is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter.

The reference velocities for the neural controller are obtained with a visual sensor.

The effectiveness of the proposed approach is tested by simulations and real-time experiments.