Efficient SLAM algorithm with hybrid visual map in an indoor environment

In this paper, we propose a scheme of generating a hybrid visual map for SLAM. The hybrid visual map has two levels of map representations: 1) the absolute map representation of highly distinctive visual planes via EKFSLAM and 2) the relative map representation of dense visual features for each visual plane via sparse information filter update. The absolute map can maintain its global consistency by matching the visual plane, the group of visual features. It improves data association and reduces the number of landmarks against individual visual features. Moreover, the relative map can reconstruct a 3-D map of visual features efficiently without loosing dense visual information. The performance of the proposed method was verified by the experimental results of consistent hybrid visual maps in an indoor environment.