Accurate global localization is crucial for autonomous navigation and planning. To this end, GPS-aided Visual-Inertial Odometry (GPS-VIO) fusion algorithms are proposed in the literature. This paper presents a novel GPS-VIO system that is able to significantly benefit from the online adaptive calibration of the rotational extrinsic parameter between the GPS reference frame and the VIO reference frame. The behind reason is this parameter is observable. This paper provides novel proof through nonlinear observability analysis. We also evaluate the proposed algorithm extensively on diverse platforms, including flying UAV and driving vehicle. The experimental results support the observability analysis and show increased localization accuracy in comparison to state-of-the-art (SOTA) tightly-coupled algorithms.

翻译：高精度全局定位对于自主导航与规划至关重要。为此，学界提出了全球定位系统辅助的视觉惯性里程计（GPS-VIO）融合算法。本文提出一种新型GPS-VIO系统，该系统能够通过在线自适应标定GPS参考系与VIO参考系之间的旋转外参参数获得显著性能提升。其核心机理在于该参数具有可观性——本文通过非线性可观性分析提供了新颖的理论证明。我们在包括飞行无人机与地面车辆在内的多平台场景中对所提算法进行了全面评估。实验验证结果支持了可观性分析结论，并在定位精度上超越了当前最先进的紧耦合算法。