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