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SLAM using visual scan-matching with distinguishable 3D points
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-1170-7162
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
2006 (English)In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vols 1-12, NEW YORK: IEEE , 2006, 4042-4047 p.Conference paper, Published paper (Refereed)
Abstract [en]

Scan-matching based on data from a laser scanner is frequently used for mapping and localization. This paper presents an scan-matching approach based instead on visual information from a stereo system. The Scale Invariant Feature Transform (SIFT) is used together with epipolar constraints to get high matching precision between the stereo images. Calculating the 3D position of the corresponding points in the world results in a visual scan where each point has a descriptor attached to it. These descriptors can be used when matching scans acquired from different positions. Just like in the work with laser based scan matching a map can be defined as a set of reference scans and their corresponding acquisition point. In essence this reduces each visual scan that can consist of hundreds of points to a single entity for which only the corresponding robot pose has to be estimated in the map. This reduces the overall complexity of the map. The SIFT descriptor attached to each of the points in the reference allows for robust matching and detection of loop closing situations. The paper presents real-world experimental results from an indoor office environment.

Place, publisher, year, edition, pages
NEW YORK: IEEE , 2006. 4042-4047 p.
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-42061DOI: 10.1109/IROS.2006.281865ISI: 000245452404026Scopus ID: 2-s2.0-34250686313ISBN: 978-1-4244-0258-8 (print)OAI: oai:DiVA.org:kth-42061DiVA: diva2:445823
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, PEOPLES R CHINA. OCT 09-13, 2006
Note
QC 20111005Available from: 2011-10-05 Created: 2011-10-05 Last updated: 2012-01-10Bibliographically approved

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Jensfelt, Patric

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Bertolli, FedericoJensfelt, PatricChristensen, Henrik I.
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