Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/88087
Type: Conference paper
Title: 6-DOF multi-session visual SLAM using anchor nodes
Author: McDonald, J.
Kaess, M.
Cadena Lerma, C.
Neira, J.
Leonard, J.
Citation: Proceedings of the 5th European Conference on Mobile Robots - ECMR 2011, 2011 / pp.69-76
Publisher: ECMR
Publisher Place: Online
Issue Date: 2011
Conference Name: European Conference on Mobile Robots (ECMR) (07 Sep 2011 - 09 Sep 2011 : Orebro, Sweden)
Statement of
Responsibility: 
John McDonald, Michael Kaess, Cesar Cadena, José Neira, John J. Leonard
Abstract: This paper describes a system for performing multisession visual mapping in large-scale environments. Multi-session mapping considers the problem of combining the results of multiple Simultaneous Localisation and Mapping (SLAM) missions performed repeatedly over time in the same environment. The goal is to robustly combine multiple maps in a common metrical coordinate system, with consistent estimates of uncertainty. Our work employs incremental Smoothing and Mapping (iSAM) as the underlying SLAM state estimator and uses an improved appearance-based method for detecting loop closures within single mapping sessions and across multiple sessions. To stitch together pose graph maps from multiple visual mapping sessions, we employ spatial separator variables, called anchor nodes, to link together multiple relative pose graphs. We provide experimental results for multi-session visual mapping in the MIT Stata Center, demonstrating key capabilities that will serve as a foundation for future work in large-scale persistent visual mapping.
RMID: 0020135946
Published version: http://aass.oru.se/Agora/ECMR2011/proceedings.html
Appears in Collections:Computer Science publications

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