Neural network MBPC for mobile robot path tracking

This paper presents a way of implementing a model-based predictive controller (MBPC) for mobile robot path tracking. The method uses a non-linear model of mobile robot dynamics and thus allows an accurate prediction of the future trajectories. Constraints on the maximum attainable speeds are also considered by the algorithm. A multilayer perceptron is used to implement the MBPC. The perceptron has been trained to reproduce the MBPC bahaviour in a supervised way. Experimental results obtained when applying the neural network controller to a TRC labmate mobile platform are given in the paper.