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Fuzzy uncertainty modeling for grid based localization of mobile robots
Univ Murcia, Dept Informat & Communicat Engn, E-30100 Murcia, Spain.
Univ Murcia, Dept Informat & Communicat Engn, E-30100 Murcia, Spain.
Örebro University, School of Science and Technology.
Örebro University, School of Science and Technology.ORCID iD: 0000-0001-8229-1363
2010 (English)In: International Journal of Approximate Reasoning, Amsterdam: Elsevier , 2010, Vol. 51, no 8, 912-932 p.Conference paper, Published paper (Other academic)
Abstract [en]

This paper presents a localization method using fuzzy logic to represent the different facets of uncertainty present in sensor data. Our method follows the typical predict-update cycle of recursive state estimators to estimate the robot's location. The method is implemented on a fuzzy position grid, and several simplifications are introduced to reduce computational complexity. The main advantages of this fuzzy logic method compared to most current ones are: (i) only an approximate sensor model is required, (ii) several facets of location uncertainty can be represented, and (iii) ambiguities in the sensor information are directly represented, thus avoiding having to solve the data association problem separately. Our method has been validated experimentally on two different platforms, a legged robot equipped with vision and a wheeled robot equipped with range sensors. The experiments show that our method can solve both the tracking and the global localization problem. They also show that this method can successfully cope with ambiguous observations, when several features may be associated to the same observation, and with robot kidnapping situations. Additional experiments are presented that compare our approach with a state-of-the-art probabilistic method. (C) 2010 Elsevier Inc. All rights reserved.

Place, publisher, year, edition, pages
Amsterdam: Elsevier , 2010. Vol. 51, no 8, 912-932 p.
Keyword [en]
Fuzzy logic, Fuzzy mathematical morphology, Robot localization, Spatial uncertainty, State estimation, RoboCup
National Category
Computer Science
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-13997DOI: 10.1016/j.ijar.2010.06.001ISI: 000282867600005OAI: oai:DiVA.org:oru-13997DiVA: diva2:388403
Conference
North American Fuzzy Information Processing Society Annual Conference NAFIPS ’2007
Note

Volume 51, Issue 8, October 2010

Available from: 2011-01-17 Created: 2011-01-17 Last updated: 2017-10-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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