Towards information-based feedback control for binaural active localization

Gabriel Bustamante (1) , Patrick Danès (1) , Thomas Forgue (1) , Ariel Podlubne (1)

1 LAAS-RAP - Équipe Robotique, Action et Perception

This paper takes place within the field of sound source localization by combining the signals sensed by a binaural head with its motor commands. Such so-called "active" schemes are known to overcome limitations occurring in the static context, such as front-back ambiguities or distance non-observability. On the basis of a stochastic filter, which approximates the posterior probability density function of the sensor-to-source situation, a feedback controller of the sensor motion is proposed so as to reduce the associated uncertainty. An information-theoretic analysis of the effect of the sensor motion on the localization uncertainty is first conducted. Then, a gradient ascent scheme is used to drive the head towards the area of minimum uncertainty (maximum information). An evaluation on simulated scenarios, as well as on data coming from real experiments, is included.

Mots clés: active localization; stochastic filtering; information theory; information based control; robot audition

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

Gabriel Bustamante, Patrick Danès, Thomas Forgue, Ariel Podlubne. Towards information-based feedback control for binaural active localization. IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2016, Shanghai, China. 5p., ⟨10.1109/ICASSP.2016.7472894⟩. ⟨hal-01969304⟩