This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model. © 2013 IEEE.