日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2603.03556

Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization

Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization

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著者: Radu-Andrei Cioaca, Paul Irofti, Cristian Rusu, Gianluca Caparra, Andrei-Alexandru Marinache, Florin Stoican

分類: cs.RO, cs.LG, cs.SY, eess.SY

原文アブストラクト

Reliable positioning in dense urban environments remains challenging due to frequent GNSS signal blockage, multipath, and rapidly varying satellite geometry. While factor graph optimization (FGO)-based GNSS-IMU fusion has demonstrated strong robustness and accuracy, most formulations remain offline. In this work, we present a real-time tightly coupled GNSS-IMU FGO method that enables causal state estimation via incremental optimization with fixed-lag marginalization, and we evaluate its performance in a highly urbanized GNSS-degraded environment using the UrbanNav dataset.