手描き地図を用いたモンテカルロ自己位置推定
Monte Carlo Localization in Hand-Drawn Maps
事前地図の代わりに非専門家が描いた手描き地図を使い、ロボットの姿勢をピクセル座標で表しつつ地図の局所的な歪みも同時推定することで自己位置推定を行う手法を提案した。
著者: Bahram Behzadian, Pratik Agarwal, Wolfram Burgard, Gian Diego Tipaldi
分類: cs.RO, cs.AI
原文アブストラクト
Robot localization is a one of the most important problems in robotics. Most of the existing approaches assume that the map of the environment is available beforehand and focus on accurate metrical localization. In this paper, we address the localization problem when the map of the environment is not present beforehand, and the robot relies on a hand-drawn map from a non-expert user. We addressed this problem by expressing the robot pose in the pixel coordinate and simultaneously estimate a local deformation of the hand-drawn map. Experiments show that we are able to localize the robot in the correct room with a robustness up to 80%
