Robust robot localization using non-speech sound in industrial environments

Abstract

Non-speech audio is a non-explored characteristic in robot localization but due to its potentiality it can yield a valuable information together with other sensorial systems. In this work, a novel robot localization method is proposed based on audio signal pattern recognition with extracted features from signal identification. To reinforce the localization, avoiding ambiguity and reducing uncertainty, a sensorial system is used aboard the robot to compute the angle between itself and the sound source. This promising methodology presents, through experimentation, robust as well as accurate results with the uncertainty bounded by the sensor measure system.