Shape recognition and orientation detection for industrial applications using ultrasonic sensors

This paper deals with a method for recognizing the form and orientation of pieces. This system uses a single pair of ultrasonic sensors to distinguish different objects and their orientations, for a set of previously learned objects. This technique utilizes the feature that small variations of position produce small variations in the value of the echo envelope parameters characterizing the ultrasonic signal. Then, neural nets are applied to learn and retrieve the necessary data in order to obtain the real position of the object. Several NN structures have been tested in order to find those that provide the best results. This system has been evaluated with symmetrical geometrical figures. Subsequently, the application was utilized in a robotic system.