DUGi

Automatic Visual Bag-of-Words for Online Robot Navigation and Mapping

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@2072@@294966

Detecting already-visited regions based on their visual appearance helps reduce drift and position uncertainties in robot navigation and mapping. Inspired from content-based image retrieval, an efficient approach is the use of visual vocabularies to measure similarities between images. This way, images corresponding to the same scene region can be associated. State-of-theart proposals that address this topic use prebuilt vocabularies that generally require a priori knowledge of the environment. We propose a novel method for appearance-based navigation and mapping where the visual vocabularies are built online, thus eliminating the need for prebuilt data. We also show that the proposed technique allows efficient loop-closure detection, even at small vocabulary sizes, resulting in a higher computational efficiency

This work was supported in part by European Union Project FP7-ICT-2011-288704 and the Spanish Ministry of Science and Innovation under Grant CTM2010-15216

Institute of Electrical and Electronics Engineers (IEEE)