Acoustic models and kalman filtering strategies for active binaural sound localization

Alban Portello (1) , Patrick Danès (1) , Sylvain Argentieri (2, 3)

1 LAAS-RAP - Équipe Robotique, Action et Perception
2 AMAC - Architectures et modèles d'Adptation et de la cognition
3 ISIR - Institut des Systèmes Intelligents et de Robotique

This paper deals with binaural sound localization. An active strategy is proposed, relying on a precise model of the dynamic changes induced by motion on the auditive perception. The proposed framework allows motions of both the sound source and the sensor. The resulting stochastic discrete-time model is then exploited together with Unscented Kalman filtering to provide range and azimuth estimation. Simulations and experiments show the effectiveness of the method.

Domaines: Robotique [cs.RO]; Intelligence artificielle [cs.AI]; Traitement du signal et de l'image [eess.SP]

Alban Portello, Patrick Danès, Sylvain Argentieri. Acoustic models and kalman filtering strategies for active binaural sound localization. IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Sep 2011, San Francisco, United States. pp.137-142, ⟨10.1109/IROS.2011.6094842⟩. ⟨hal-03196429⟩