Visual odometer system to build feature based maps for mobile robot navigation

Abstract

This paper presents a visual odometer system for mobile robot position correction. The developed algorithm detects the same Speeded Up Robust Features (SURF) on the stereo pair images to obtain three dimensional point clouds at every robot location. The algorithm tracks the displacement of the identical features viewed from different positions to compute the robots positions. The displacements between the point clouds are computed with the use of the Iterative Closest Point (ICP) algorithm. The ICP is used also to register the landmarks in the feature based map of the entire environment. The results of an indoor office environment experiments are shown.