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arXiv · 1602.08139

Robust Localization and Tracking of Simultaneous Moving Sound Sources Using Beamforming and Particle Filtering

Jean-Marc Valin·François Michaud·Jean Rouat
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Abstract

Mobile robots in real-life settings would benefit from being able to localize and track sound sources. Such a capability can help localizing a person or an interesting event in the environment, and also provides enhanced processing for other capabilities such as speech recognition. To give this capability to a robot, the challenge is not only to localize simultaneous sound sources, but to track them over time. In this paper we propose a robust sound source localization and tracking method using an array of eight microphones. The method is based on a frequency-domain implementation of a steered beamformer along with a particle filter-based tracking algorithm. Results show that a mobile robot can localize and track in real-time multiple moving sources of different types over a range of 7 meters. These new capabilities allow a mobile robot to interact using more natural means with people in real life settings.

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Jean-Marc Valin, François Michaud, Jean Rouat. 2016-02-25. Robust Localization and Tracking of Simultaneous Moving Sound Sources Using Beamforming and Particle Filtering. https://doi.org/10.1016/j.robot.2006.08.004

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