Stereo vision based SLAM in outdoor environments

Abstract

Simultaneous localization and mapping is a well studied problem as it is considered by many to be an essential capability for autonomous robots. In this paper, we present an algorithm using a stereo camera based on Rao-Blackwelltion particle filter, It can realize three dimensional stereo vision SLAM for mobile robot in unknown outdoor environments. Firstly, we determine the initial motion estimation between two adjacent frames through the multiple view geometry utilizing the matched SIFT point pairs. Then, the 3D positions of landmarks are constructed directly through triangulation methodology. With accurate data association, the camera's state and the landmark positions are updated recursively. Finally, an efficient particle resamping algorithm MPR (the modified particle resampling algorithm) is proposed to deal with the degeneracy of particles.