2A2-T02 幾何的整合性に基づく視野画像列を用いた自己位置推定の研究(移動ロボットの自己位置推定と地図構築)

Abstract

Robot self localization is a fundamental problem for autonomous robot navigation. The objective is to take a view image acquired by the robot as query input and to estimate the self pose with respect to view images in a map database. In this paper, we focus on the standard SIFT features based self localization framework and improve its robustness by means of geometric verification of the configuration of SIFT local features between images. We demonstrate the effectiveness of the proposed method via self localization experiments.