Structureless VIO

Visual odometry (VO) is typically considered as a chicken-and-egg problem, as the localization and mapping modules are tightly-coupled. The estimation of 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 solution that does not require a map has 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.

@article{song2025_2505.12337,
  title={ Structureless VIO },
  author={ Junlin Song and Miguel Olivares-Mendez },
  journal={arXiv preprint arXiv:2505.12337},
  year={ 2025 }
}