オルソモザイク地図を用いた空中・地上移動ロボットの協調自己位置推定
Collaborative Localization of Aerial and Ground Mobile Robots through Orthomosaic Map
ドローンが作成したオルソモザイク地図と地上ロボットの地図をテンプレートマッチングで照合し、パーティクルフィルタで地上ロボットの自己位置を推定する協調SLAM手法を提案した論文。
著者: Xuecheng Xu, Zexi Chen, Jiaxin Guo, Yue Wang, Yunkai Wang, Rong Xiong
分類: cs.RO
原文アブストラクト
With the deepening of research on the SLAM system, the possibility of cooperative SLAM with multi-robots has been proposed. This paper presents a map matching and localization approach considering the cooperative SLAM of an aerial-ground system. The proposed approach aims to help precisely matching the map constructed by two independent systems that have large scale variance of viewpoints of the same route and eventually enables the ground mobile robot to localize itself in the global map given by the drone. It contains dense mapping with Elevation Map and software "Metashape", map matching with a proposed template matching algorithm, weighted normalized cross-correlation (WNCC) and localization with particle filter. The approach enables map matching for cooperative SLAM with the feasibility of multiple scene sensors, varies from stereo cameras to lidars, and is insensitive to the synchronization of the two systems. We demonstrate the accuracy, robustness, and the speed of the approach under experiments of the Aero-Ground Dataset.
