Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/88080
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Type: Journal article
Title: RSLAM: a system for large-scale mapping in constant-time using stereo
Author: Mei, C.
Sibley, G.
Cummins, M.
Newman, P.
Reid, I.
Citation: International Journal of Computer Vision, 2011; 94(2):198-214
Publisher: Springer Verlag
Issue Date: 2011
ISSN: 0920-5691
1573-1405
Statement of
Responsibility: 
Christopher Mei, Gabe Sibley, Mark Cummins, Paul Newman, Ian Reid
Abstract: Large scale exploration of the environment requires a constant time estimation engine. Bundle adjustment or pose relaxation do not fulfil these requirements as the number of parameters to solve grows with the size of the environment. We describe a relative simultaneous localisation and mapping system (RSLAM) for the constant-time estimation of structure and motion using a binocular stereo camera system as the sole sensor. Achieving robustness in the presence of difficult and changing lighting conditions and rapid motion requires careful engineering of the visual processing, and we describe a number of innovations which we show lead to high accuracy and robustness. In order to achieve real-time performance without placing severe limits on the size of the map that can be built, we use a topo-metric representation in terms of a sequence of relative locations. When combined with fast and reliable loop-closing, we mitigate the drift to obtain highly accurate global position estimates without any global minimisation. We discuss some of the issues that arise from using a relative representation, and evaluate our system on long sequences processed at a constant 30–45 Hz, obtaining precisions down to a few meters over distances of a few kilometres.
Keywords: SLAM; Stereo; Tracking; Loop closing; SIFT
Rights: © Springer Science+Business Media, LLC 2010
RMID: 0020131086
DOI: 10.1007/s11263-010-0361-7
Appears in Collections:Computer Science publications

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