A new method for self-supervised sensorimotor learning of sound source localization is presented, that allows a simulated listener to learn online an auditorimotor map from the sensorimotor experience provided by an auditory evoked behavior. The map represents the auditory space and is used to estimate the azimuthal direction of sound sources. The learning mainly consists in non-linear dimensionality reduction of sensorimotor data. Our results show that an auditorimotor map can be learned, both from real and simulated data, and that the online learning leads to accurate estimations of azimuthal sources direction.

This paper deals with the biomimetic design of a humanoid head prototype. This prototype is developed in order to offer some mechanical device for multimodality objectives, and to demonstrate the importance of uncoupled eyes mechanism in humanoid head function. Indeed, the prototype development is based on our understanding of the humans head properties in the filed of visual and vestibular capabilities. The final prototype will have 3 DOF for each eye and 2 DOF for the neck. The developed device based as on one dof for each eye and one dof for the neck is able to show the vestibular ocular reflex (VOR) and the target tracking (TT) in real time. To carry out all these capabilities, a generic visual perception processor is developed and used. The first experiments on 3 DOF mechanism are given