Localizing an intermittent and moving sound source using a mobile robot

Quan V. Nguyen 1 Francis Colas 1 Emmanuel Vincent 2 François Charpillet 1
1 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
2 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : This paper addresses the problem of localizing and tracking one intermittent, moving sound source using a microphone array on a mobile robot. Robot motion provides a solution for estimating the distance to the source and avoiding front-back ambiguity. We propose a mixture Kalman filter (MKF) framework in order to fuse the robot motion information and the measurements taken at different poses of the robot. Experiments and statistical results demonstrate the ability of the proposed method to track one intermittent sound source in a reverberant environment where false measurements of the source angle of arrival (AoA) and the source activity often occur compared to a method that does not consider tracking source activity into account.
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Submitted on : Tuesday, August 16, 2016 - 5:35:28 PM
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Quan V. Nguyen, Francis Colas, Emmanuel Vincent, François Charpillet. Localizing an intermittent and moving sound source using a mobile robot. International Conference on Intelligent Robots and Systems (IROS), Oct 2016, Deajeon, South Korea. ⟨hal-01354006⟩

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