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Framework for evaluating intrinsic kidnapping detection methods in Monte Carlo Localisation
Örebro University, School of Science and Technology.
2021 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
Abstract [sv]

Det har projektet presenterar ett programmatiskt ramverk for att evalueraoch simulera upptackningsmetoder till ett lokaliseringsproblem kallat "The kidnappedrobot problem". Ramverket erbjuder en miljo med olika varldar darsymmetri uttrycker sig till olika grader dar man kan utfora simuleringar. Enrobot med en 360 distanssensor ror sig for att navigera sig sjalv i miljonmed hjalp utav Monte Carlo Lokalisering. I miljon kan roboten bli utsatt for"The Kidnapped Robot Problem" igenom olika tillvagagangssatt sasom driftandeodometri och teleportering, detta resulterar i ett ramverk dar man kansimulera och evaluera olika upptackningsmetoder. En rad argument presenterastill varfor ROS och den tillgangliga ROS-noden ROS-amcl inte ar en passandemiljo for att utfora experiment av denna sorten i. Valideringsexperiment presenterasdar ramverket testas och utvarderas, vidare ar aven tva stycken publiceradelosningar till att upptacka kidnappning implementerade och testade iramverket. Problemet "The Kidnapped Robot Problem" diskuteras i kontextenav Monte Carlo Lokalisering och det varde som upptackningsmetoder for medsig i praktiken lyfts fram tillsammans med en forklaring till andra faktorer anfysisk kidnappning som gor problemet mycket relevant.

Abstract [en]

This thesis presents a framework for evaluating intrinsic kidnapped robot problemdetection methods. The framework implements a landmark based environmentin which a robot with a 360range  nder sensor acts and navigates itself tobe subjected to the kidnapped robot problem through di erent causes such asteleportation and drifting odometry. A set of arguments are presented arguingagainst performing the task in ROS using the ROS-amcl package. Validationexperiments are performed on the framework and through surveying the state ofthe art solutions for the kidnapped robot problem, two easy to use kidnappingdetection methods are implemented and tested. The kidnapped robot problemin Monte Carlo Localisation(MCL) is discussed and the practical importance ofthe problem as well as possible causes are explained and discussed.

Place, publisher, year, edition, pages
2021. , p. 47
Keywords [sv]
Kidnapped Robot Problem, Kidnapped Robot Problem upptackning, Monte Carlo Lokalisering(MCL), Bayes Filter, ROS-AMCL, Partikel Filter
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-94317OAI: oai:DiVA.org:oru-94317DiVA, id: diva2:1593895
Subject / course
Computer Engineering
Supervisors
Examiners
Available from: 2021-09-14 Created: 2021-09-14 Last updated: 2021-09-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
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  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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