Generating a consistent global map under intermittent mapping conditions for large-scale vision-based navigation

Localization is the process to compute sensor poses based on vision technologies such as visual Simultaneous Localization And Mapping (vSLAM). It can generally be applied to navigation systems . To achieve this, a global map is essential such that the relocalization process requires a single consistent map represented with an unified coordinate system. However, a large-scale global map cannot be created at once due to insufficient visual features at some moments. This paper presents an interactive method to generate a consistent global map from intermittent maps created by vSLAM independently via global reference points. First, vSLAM is applied to individual image sequences to create maps independently. At the same time, multiple reference points with known latitude and longitude are interactively recorded in each map. Then, the coordinate system of each individual map is converted into the one that has metric scale and unified axes with the reference points. Finally, the individual maps are merged into a single map based on the relative position of each origin. In the evaluation, we show the result of map merging and relocalization with our dataset to confirm the effectiveness of our method for navigation tasks. In addition, the report on participating in the navigation competition in a practical environment is also discussed.