グラフ理論的対応付けによる単発グローバル位置推定
Single-Shot Global Localization via Graph-Theoretic Correspondence Matching
クエリと事前地図のインスタンスをグラフ理論的にマッチングし、最大クリーク問題に基づいて単発でグローバル位置推定を行う手法を提案した論文。
著者: Shigemichi Matsuzaki, Kenji Koide, Shuji Oishi, Masashi Yokozuka, Atsuhiko Banno
分類: cs.RO, cs.CV
原文アブストラクト
This paper describes a method of global localization based on graph-theoretic association of instances between a query and the prior map. The proposed framework employs correspondence matching based on the maximum clique problem (MCP). The framework is potentially applicable to other map and/or query modalities thanks to the graph-based abstraction of the problem, while many of existing global localization methods rely on a query and the dataset in the same modality. We implement it with a semantically labeled 3D point cloud map, and a semantic segmentation image as a query. Leveraging the graph-theoretic framework, the proposed method realizes global localization exploiting only the map and the query. The method shows promising results on multiple large-scale simulated maps of urban scenes.
