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Learning to Detect Loop Closure from Range Data
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-3450-988X
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
University of Sydney, Australian Centre for Field Robotics.
University of Sydney, Australian Centre for Field Robotics.
2009 (English)In: Proceedings of '09 IEEE International Conference on Robotics and Automation, 2009, 15-22 p.Conference paper, Published paper (Refereed)
Abstract [en]

Despite significant developments in the Simultaneous Localisation and Mapping (SLAM) problem, loop closure detection is still challenging in large scale unstructured environments. Current solutions rely on heuristics that lack generalisation properties, in particular when range sensors are the only source of information about the robot's surrounding environment. This paper presents a machine learning approach for the loop closure detection problem using range sensors. A binary classifier based on boosting is used to detect loop closures. The algorithm performs robustly, even under potential occlusions and significant changes in rotation and translation. We developed a number of features, extracted from range data, that are invariant to rotation. Additionally, we present a general framework for scan-matching SLAM in outdoor environments. Experimental results in large scale urban environments show the robustness of the approach, with a detection rate of 85% and a false alarm rate of only 1%. The proposed algorithm can be computed in real-time and achieves competitive performance with no manual specification of thresholds given the features.

Place, publisher, year, edition, pages
2009. 15-22 p.
Keyword [en]
Learning and Adaptive Systems, Recognition, SLAM
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-18518DOI: 10.1109/ROBOT.2009.5152495ISI: 000276080401011ISBN: 978-1-4244-2789-5 (print)OAI: oai:DiVA.org:liu-18518DiVA: diva2:220135
Conference
'09 IEEE International Conference on Robotics and Automation, Kobe, Japan, May, 2009
Projects
CADICS
Available from: 2009-06-08 Created: 2009-05-29 Last updated: 2014-03-27Bibliographically approved

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Granström, KarlCallmer, Jonas

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