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Computationally effective stereovision SLAM
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
Computer and System Sciences, Sapienza University of Rome, Italy.
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
2010 (English)In: 2010 IEEE International Conference on Imaging Systems and Techniques, IST 2010 - Proceedings, IEEE , 2010, 458-463 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated Cellular Automata (CA)-based enhancement stage. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image sets are provided and analyzed.

Place, publisher, year, edition, pages
IEEE , 2010. 458-463 p.
Keyword [en]
Autonomous robotics, Cellular automata, Feature matching, SLAM, Stereovision, Area measurement, Calculation scheme, Image sets, Moving robots, Scale and rotation, Simultaneous localization and mapping algorithms, SLAM algorithm, Speeded up robust features, Stereo cameras, Stereo correspondences, Algorithms, Imaging systems, Pattern recognition systems, Robotics, Robots, Sensors, Stereo vision, Image matching
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-50990DOI: 10.1109/IST.2010.5548507Scopus ID: 2-s2.0-77957825898ISBN: 978-142446494-4 (print)OAI: oai:DiVA.org:kth-50990DiVA: diva2:463174
Conference
2010 IEEE International Conference on Imaging Systems and Techniques, IST 2010; Thessaloniki; 1 July 2010 through 2 July 2010
Projects
Vision and Chemiresistor Equipped Web-connected Finding Robots (View-Finder), FP6-IST-2006-045541
Note
QC 20111209Available from: 2011-12-08 Created: 2011-12-08 Last updated: 2011-12-09Bibliographically approved

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Total: 31 hits
CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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Language
  • de-DE
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  • fi-FI
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  • Other locale
More languages
Output format
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  • asciidoc
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