Neural Networks for Sonar and Infrared Sensors Fusion

The main goal of our work is to have a robot navigating in unknown and not specially structured environments, and performing delivery like tasks. This robot has both unreliable sonar and infrared sensors. To cope with unreliability a sensor fusion method is needed. The main problem when applying classical fusion methods is that there is no a priori model of the environment, just because the robot first carries on a map building process. There exist some simple methods for sensor fusion but, as we show, they do not address all the specific issues of our desired robot task. This way, we use neural networks for such fusion, and so we obtain more reliable data. We discuss some important points related to the training procedure of neural networks and the results we obtained.