Skip to Main content Skip to Navigation
New interface
Conference papers

Interactive learning of visual topological navigation

Abstract : We present a topological navigation system that is able to visually recognize the different rooms of an apartment and guide a robot between them. Specifically tailored for small entertainment robots, the system relies on vision only and learns its navigation capabilities incrementally by interacting with a user. This continuous learning strategy makes the system particularly adaptable to environmental lighting and structure modifications. From the computer vision point of view, the system uses a purely appearance-based image representation called bag of visual words, without any metric information. This representation was adapted to the incremental context of robotics and supplemented by active perception to enhance performances. Empirical validation on real robots and on the publicly available INDECS image database are presented.
Document type :
Conference papers
Complete list of metadata

Cited literature [28 references]  Display  Hide  Download
Contributor : David Filliat Connect in order to contact the contributor
Submitted on : Tuesday, November 15, 2011 - 3:03:55 PM
Last modification on : Wednesday, May 11, 2022 - 12:06:05 PM
Long-term archiving on: : Friday, November 16, 2012 - 10:56:43 AM


Publisher files allowed on an open archive




David Filliat. Interactive learning of visual topological navigation. International Conference on Intelligent Robots and Systems (IROS), 2008, France. pp.248 - 254, ⟨10.1109/IROS.2008.4650681⟩. ⟨hal-00641356⟩



Record views


Files downloads