Abstract
In this paper we present a highly scalable vision-based localization and mapping method using image collections. A topological world representation is created online during robot exploration by adding images to a database and maintaining a link graph. An efficient image matching scheme allows real-time mapping and global localization. The compact image representation allows us to create image collections containing millions of images, which enables mapping of very large environments. A path planning method using graph search is proposed and local geometric information is used to navigate in the topological map. Experiments show the good performance of the image matching for global localization and demonstrate path planning and navigation.
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