MODELADO ESTOCÁSTICO DE UN SONAR ROTATIVO: UN CASO ORIENTADO A LA CONSTRUCCIÓN PROBABILÍSTICA DE MAPAS DE HITOS PUNTUALES

Ultrasonic sensing is a well suited cost-benefit technique used in mobile robotics. Nevertheless, this sensor type has a key drawback: its very Wide beam. This fact causes that this sensor becomes useless in the environment map building process. Another problem attached with this sensor is that it offers very little facilities for landmark extraction and object recognition. This problem is known as Matching. In this paper we introduce an ultrasonic sensor capable to extract wall or corner from an indoor environment, as well as to reduce the angle uncertainty, on the based of echo amplitude reaching the transducer. Moreover, we developed the stochastic model for this sensor as well as a matching algorithm for using this device as main observation element for probabilistic SLAM (Simultaneous Localization And Mapping).