Building autonomous mobile robots has been a primary aim of robotics and artificial intelligence. Artificial neural networks are capable of performing the different aspecis of autonomous drmng, such as collision-free motions, avoiding obstacles, mapping and planning of path. This paper describes the global architecture of the neural system for autonomous control of a mobile robot. Such neural system has the ability for self-training and self-organizing. The purpose of this paper is to present the key ideas and approaches underlying our research in this area
