Simultaneous Localization and Mapping Using Extended Kalman Filter

Abstract

In this study an offline statistical estimation algorithm based on Extended Kalman Filter method is developed to solve the SLAM (Simultaneous Localization and Map Building) problem. For the application, a robot equipped with only simple and cheap sensors is used. Two of the most frequent problems in SLAM algorithms which are known as loop closing and data association are effectively solved by Extended Kalman Filter method.