By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tudor Nicosevici ; Computer Vision and Robotics Group , University of Girona, Girona, Spain ; Rafael Garcia

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-the-art 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.

Published in:

IEEE Transactions on Robotics  (Volume:28 ,  Issue: 4 )