Expert systems and other conventional approaches have proven to be of limited ability in addressing the problem of robot navigation. Recent advances in neural network technology, in particular, powerful learning paradigms and neuro-computer hardware, could provide crucial tools for developing improved algorithms and computational hardware for robot navigation. Several researchers have designed nonlinear controllers using neural networks for precise navigation and positioning of the robotic vehicles around fixed and moving objects. This paper reviews various neural net applications in the areas of robot control. Autonomous land vehicles, and underwater robotic vehicles. The results show the feasibility of using neuro-controllers for these robotic vehicles in the presence of unpredictable changes int eh dynamics of the vehicle and its environment.