English

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

Robotics 2026-03-05 v1 Machine Learning Systems and Control Systems and Control

Abstract

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.

Cite

@article{arxiv.2603.03556,
  title  = {Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization},
  author = {Radu-Andrei Cioaca and Paul Irofti and Cristian Rusu and Gianluca Caparra and Andrei-Alexandru Marinache and Florin Stoican},
  journal= {arXiv preprint arXiv:2603.03556},
  year   = {2026}
}
R2 v1 2026-07-01T11:02:11.423Z