Robust localization and tracking of simultaneous moving sound sources using beamforming and particle filtering

Authors:
Jean-Marc Valin;François Michaud;Jean Rouat
Affiliations:
CSIRO ICT Centre, Marsfield, NSW 2122, Australia and Department of Electrical Engineering and Computer Engineering, Université de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada;Department of Electrical Engineering and Computer Engineering, Université de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada;Department of Electrical Engineering and Computer Engineering, Université de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada
Venue:
Robotics and Autonomous Systems
Year:
2007

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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 m. These new capabilities allow a mobile robot to interact using more natural means with people in real-life settings.