Year: 2013
Type: article
Abstract: Cognitive developmental robotics unites machine learning and neuroscience with the aim of creating robots which display the robustness and efficiency of human cognition. This document proposes a novel method for acquiring a visuomotor mapping for hand-eye coordination. This model is trained on the iCub humanoid robot and used for smooth control of reaching. Applications of this model to sensorimotor associative learning are examined. In addition, a derivation of the self-organizing map from neural dynamics is presented. This dissertation is part of an overarching goal of developing a platform-independent model of intelligent systems.
Author: Lydia Majure
Language: English
Topic: Motor Control and Adaptation
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2263003514