F3Loc: Fusion and Filtering for Floorplan Localization

Figure 1. Floorplan localization. We propose a novel probabilistic model for localization within a floorplan consisting of a data-driven observation (a,b) and a temporal filtering module (c). Evidence is estimated as a 1D-range image from a single (a) and a few consecutive RGB images (b). A learned soft selection module combines the output from the complementary cues. The observation likelihood is integrated over time by an efficient SE2 histogram filter to deliver the pose posterior. Our system achieves rapid and accurate sequential localization, outperforming the state-of-the-art in recall and localization speed, while operating on consumer hardware.