EKF-SLAM and Machine Learning Techniques for Visual Robot Navigation

Abstract

In this work we propose the use of machine learning techniques to improve Simultaneous Localization and Mapping (SLAM) using an extended Kalman filter (EKF) and visual information for robot navigation. We are using the Viola and Jones approach for looking specific visual landmarks in environment. The landmarks are used to improve the robot localization in the EKF-SLAM system. Our experiments validate the efficiency of our algorithm.