Introduction

Contents

This book describes the design and implementation of a vision-based Simultaneous Localisation And Mapping (SLAM) system using an extended model of the rodent hippocampus, and a mapping algorithm that integrates with this system to provide goal recall and environment adaptation capabilities. Computational models of biological systems have traditionally had limited mapping and navigation capabilities when implemented on real robots. Conventional probabilistic techniques can solve specific components of the problem such as SLAM, but do not provide an integrated solution to the entire problem of exploring, mapping, navigating to goals, and adapting to change. The aim of this research was to demonstrate that by analysing and extending models of the rodent hippocampus within a pragmatic robotics context, it is possible to create a biologically inspired model that can solve many of the key mapping and navigation problems.