Online visual motion estimation using FastSLAM with SIFT features

Abstract

This paper describes a technique to estimate the 3D motion of a vehicle using odometric sensors and a stereo camera. The algorithm falls into the category of simultaneous localization and mapping as a large database of visual landmarks is created. The algorithm has been field tested online on a rover traversing loose terrain in the presence of obstacles. The resulting position estimation errors are between 0.5% and 4% of distance travelled, a significant improvement over odometry alone.