Global Localization with Place Recognition Based on Image Similarity

Abstract

In this paper, we propose a new localization method combining visual place recognition with MCL. It is difficult for conventional localization methods to localize in the absence of prior position information. This is especially true in environments with poor geometric features because most of them rely on only geometric information when they localize. Therefore we reflected the results of similarity-based visual place recognition to MCL. MCL is a probabilistic and geometric localization method using LiDAR. An experiment was conducted in a simulation environment to compare MCL using only geometric information and the proposed method using both geometric and visual information. The experimental results show that our method is superior in terms of accuracy and convergence speed.