Single-Shot Global Localization via Graph-Theoretic Correspondence Matching

• URL: http://arxiv.org/abs/2306.03641v1
• Date: Tue, 6 Jun 2023 12:52:07 GMT
• Title: Single-Shot Global Localization via Graph-Theoretic Correspondence Matching
• Authors: Shigemichi Matsuzaki, Kenji Koide, Shuji Oishi, Masashi Yokozuka, Atsuhiko Banno
• Abstract summary: The proposed framework employs correspondence matching based on the maximum clique problem (MCP) We implement it with a semantically labeled 3D point cloud map, and a semantic segmentation image as a query. The method shows promising results on multiple large-scale simulated maps of urban scenes.
• Score: 16.956872056232633
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 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.

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