GPS-VIO Fusion with Online Rotational Calibration

TL;DR

This paper introduces a GPS-VIO fusion system with online rotational calibration, improving localization accuracy by leveraging the observability of the extrinsic parameter, validated through analysis and extensive experiments.

Contribution

The paper presents a novel GPS-VIO fusion approach that performs online calibration of the rotational extrinsic parameter, supported by nonlinear observability analysis.

Findings

Enhanced localization accuracy over state-of-the-art methods

Validated observability of the rotational extrinsic parameter

Effective on diverse platforms including UAVs and vehicles

Abstract

Accurate global localization is crucial for autonomous navigation and planning. To this end, various 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 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.