Consistent Localization for Autonomous Robots With Inter-Vehicle GNSS Information Fusion

Abstract

In this letter, we reveal a new precise localization framework based on inter-vehicle GNSS information fusion (IGIF) for autonomous robot systems. In this framework, we derive a new hybrid GNSS filter (HGF) using information from both onboard sensors and the inter-vehicle network, and a consistency checking (CC) method to improve the system reliability. The main novelty of the proposed method is the fusion of ionosphere-free (IF) and double differenced (DD) combinations to improve the global positioning accuracy of robots and the two-level probabilistic detection of erroneous inter-vehicle measurements. A real-world experiment was conducted and it turned out that our method provided more consistent, continuous, and accurate position estimation than the state-of-the-art methods while only requiring low communication bandwidth.