  The aim of this work is to build a cognitive model for the humanoid robot,
especially, we are interested in the navigation and mapping on the humanoid
robot. The agents used are the Alderbaran NAO robot. The framework is
effectively applied to the integration of AI, computer vision, and signal
processing problems. Our model can be divided into two parts, cognitive mapping
and perception. Cognitive mapping is assumed as three parts, whose
representations were proposed a network of ASRs, an MFIS, and a hierarchy of
Place Representations. On the other hand, perception is the traditional
computer vision problem, which is the image sensing, feature extraction and
interested objects tracking. The points of our project can be concluded as the
following. Firstly, the robotics should realize where it is. Second, we would
like to test the theory that this is how humans map their environment. The
humanoid robot inspires the human vision searching by integrating the visual
mechanism and computer vision techniques.
