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Mécanismes d'inspiration corticale pour l'apprentissage et la représentation d'asservissements sensori-moteurs en robotique

Abstract : This thesis aims at setting up a sensory-motor loop, that can be used in robotics, while using biologically, and more precisely cortically, inspired algorithms. We hope this method allows to reproduce the robustness, structural uniformity and adaptability that are some of the most remarkable qualities of the cortical substrate. From a computational point of view, our model is based on extensions of the cellular automata. This brings us to program units within maps, each of these maps representing a biological cortical map. We design updating mechanisms for these units leading to emergent effects within the maps, so that sensory-motor loops stand. In addition, we think that perceiving is the same as preparing an action. We therefore have to balance our holistic view of perception with the fact that the multiple modalities of perception are each represented on a different map in our model, as it is the case in the cortex. That is the reason why the major part of this thesis aims at creating a linking algorithm between the modal maps , while keeping the number of link low for computational reasons. This creates strong constraints on both the organization and the learning algorithm of our modal maps. While we used strictly local computations, each unit, in each map in our model, realizes a compromise between local influences of the map and influences from the other maps, that allow our model to keep a multi-modal coherence.
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Theses
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http://docnum.univ-lorraine.fr/prive/SCD_T_2006_0147_MENARD.pdf
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https://hal.univ-lorraine.fr/tel-01746569
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Submitted on : Thursday, March 29, 2018 - 10:40:27 AM
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Olivier Ménard. Mécanismes d'inspiration corticale pour l'apprentissage et la représentation d'asservissements sensori-moteurs en robotique. Autre [cs.OH]. Université Henri Poincaré - Nancy 1, 2006. Français. ⟨NNT : 2006NAN10147⟩. ⟨tel-01746569⟩

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