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Autonomous Robots

Erschienen in:

15.06.2017

An information based feedback control for audio-motor binaural localization

verfasst von: Gabriel Bustamante, Patrick Danès, Thomas Forgue, Ariel Podlubne, Jérôme Manhès

Erschienen in: Autonomous Robots | Ausgabe 2/2018

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Abstract

In static scenarios, binaural sound localization is fundamentally limited by front-back ambiguity and distance non-observability. Over the past few years, “active” schemes have been shown to overcome these shortcomings, by combining spatial binaural cues with the motor commands of the sensor. In this context, given a Gaussian prior on the relative position to a source, this paper determines an admissible motion of a binaural head which leads, on average, to the one-step-ahead most informative audio-motor localization. To this aim, a constrained optimization problem is set up, which consists in maximizing the entropy of the next predicted measurement probability density function over a cylindric admissible set. The method is appraised through geometrical arguments, and validated in simulations and on real-life robotic experiments.

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Consider again the dynamic equation (2) with no dynamic noise, and assume that the posterior covariance \(\overline{P}_{k|k}\) of the full state \(X_k\) (defined in \(\mathbb {R}^3\)) is \(\overline{P}_{k|k} = {{\mathrm{diag}}}(0,P_{k|k})\). As the vector \(R^T(\phi ){T}\) is constant, the next “full” predicted covariance \(\overline{P}_{k+1|k}\) writes as \(\overline{P}_{k+1|k} = R^T(\phi )\overline{P}_{k|k}R(\phi )\), with \(R(\phi ) = {{\mathrm{diag}}}(1,r(\phi ))\), and \({|R(\phi )|{}={}|r(\phi )|{}={}1}\). Consequently, \(\overline{P}_{k+1|k} = {{\mathrm{diag}}}(0,P_{k+1|k})\) with \({|P_{k+1|k}|=|r^T(\phi )P_{k|k}r(\phi )|=|P_{k|k}|}\).

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Titel: An information based feedback control for audio-motor binaural localization
verfasst von: Gabriel Bustamante
Patrick Danès
Thomas Forgue
Ariel Podlubne
Jérôme Manhès
Publikationsdatum: 15.06.2017
Verlag: Springer US
Erschienen in: Autonomous Robots / Ausgabe 2/2018
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI: https://doi.org/10.1007/s10514-017-9639-8

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