Representation of map model for mobile robot based on hippocampus place cell functionality

摘要

Mapping is one of important issue in robotics. In this paper a new vision based odometery free algorithm for representing environment map is proposed. Our contribution is providing a model based on two important types of brain cells. Place cells in hippocampus play main role in mapping and entorhinal cortex layer cells reacting to image features provide main portion of positional cells input. Our contribution is modelling these two important types of cells by Kohonene self-organizing map. Considering Gabor filter compatibility in determining image texture, V1 visual layer is modelled by a Gabor filter histogram and the output of filter on input images is feeding to a Kohonene self-organizing map that models entorhinal cortex layer cells. The model is implemented on real robot equipped with an omni-directional camera in a real 10*30 meter environment. The results showed that the robot can make an appropriate map and determine its location in drawn map.