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.
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Dimitrova-Grekow, T., Jarczewski, M. (2014). Sonar Method of Distinguishing Objects Based on Reflected Signal Specifics. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_52
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DOI: https://doi.org/10.1007/978-3-319-08326-1_52
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08325-4
Online ISBN: 978-3-319-08326-1
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