A Cognitive Map Learning Model Based on Hippocampal Place Cells

Abstract

Aiming at the environment cognition and navigation problem of autonomous mobile robots in unknown environment, a cognitive map learning model is proposed based on hippocampal place cells, which can memorize and map surroundings. The model uses the self-organizing feature map as the basic structure. Each hippocampal place cell is represented by a neural node. The robot builds up the hippocampal place cells layer through environment exploration. The simulation results show that the model has self-learning ability, which enables robots to acquire environment knowledge and establish a complete cognitive map gradually like human beings and animals, making the robot's environment cognition and navigation process become more bionic and intelligent.