Sonar method of distinguishing objects based on reflected signal specifics

Abstract

This paper presents a method of pattern recognition based on sonar signal specificity. Environment data is collected by a Lego Mindstorms NXT mobile robot using a static sonar sensor. The primary stage of research includes offline data processing. As a result, a set of object features enabling effective pattern recognition was established. The most essential features, reflected into object parameters are described. The set of objects consists of two types of solids: parallelepipeds and cylinders. The main objective is to set clear and simple rules of distinguishing the objects and implement them in a real-time system: NXT robot. The tests proved the offline calculations and assumptions. The object recognition system presents an average accuracy of 86%. The experimental results are presented. Further work aims to implement in mobile robot localization: building a relative confidence degree map to define vehicle location. © 2014 Springer International Publishing.