日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

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arXiv:2505.12337

Structureless VIO

Structureless VIO

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著者: Junlin Song, Miguel Olivares-Mendez

分類: cs.RO, cs.CV

原文アブストラクト

Visual odometry (VO) is typically considered as a chicken-and-egg problem, as the localization and mapping modules are tightly-coupled. The estimation of a visual map relies on accurate localization information. Meanwhile, localization requires precise map points to provide motion constraints. This classical design principle is naturally inherited by visual-inertial odometry (VIO). Efficient localization solutions that do not require a map have not been fully investigated. To this end, we propose a novel structureless VIO, where the visual map is removed from the odometry framework. Experimental results demonstrated that, compared to the structure-based VIO baseline, our structureless VIO not only substantially improves computational efficiency but also has advantages in accuracy.