The abilities of mobile robots depend greatly on the performance of basic skills such as vision and localization. Although great progress has been made in the 4-Legged league in the past years, the performance of many of those approaches completely depends on the artificial environment conditions established on a 4-Legged soccer field. In this article, an algorithm is introduced that can provide localization information based on the natural appearance of the surroundings of the field. The algorithm starts making a scan of the surroundings by turning head and body of the robot on a certain spot. The robot learns the appearance of the surroundings at that spot by storing color transitions at different angles in a panoramic index. The stored panoramic appearance can be used to determine the rotation (including a confidence value) relative to the learned spot for other points on the field. The applicability of this kind of localization for more natural environments is demonstrated in two environments other than the official 4-Legged league field.
展开▼
