Vision-based Simultaneous Localization and Map Building: Stereo and mono SLAM

Abstract

The simultaneous operation of localization capability which serves to navigation of an autonomous robot and map building mechanism which provides an environmental model is called SLAM (Simultaneous Localization and Map Building). While various sensors are used for this algorithm, vision-based algorithms are relatively new and have attracted more attention in recent years. In this work, while a Visual SLAM algorithm utilizing Extended Kalman Filter is introduced, the two main branches, mono and stereo SLAM algorithms, are also compared.