SchurVINS: Schur Complement-Based Lightweight Visual Inertial Navigation System

arXiv:2312.01616v2 Announce Type: replace
Abstract: Accuracy and computational efficiency are the most important metrics to Visual Inertial Navigation System (VINS). The existing VINS algorithms with either high accuracy or low computational complexity, are difficult to provide the high precision localization in resource-constrained devices. To this end, we propose a novel filter-based VINS framework named SchurVINS, which could guarantee both high accuracy by building a complete residual model and low computational complexity with Schur complement. Technically, we first formulate the full …

arxiv cs.cv cs.ro navigation type visual