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Markov lokalisering
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
2002 (Swedish)Independent thesis Basic level (degree of Bachelor)Student thesis
Abstract [sv]
In this paper the theory and an implementation of Markov localization will be presented. Markov localization is a global localization method. By global localization of robots we mean that a robot is capable of locating its position in a known environment, without knowledge of its initial position. Markov localization divides the environment in x, y and rotation. For every position in the grids a probability is continuously calculated. This specifies the probability of the robot being at the specified position. If Markov localization should work in changeable environments, filters are needed. In this paper different filters are described and tested. All tests are done in a own implemented simulator. The tests show good results of this method, but it has both high time and memory demands. To be able to decrease the time some optimizations are described and one of them is tested.
Place, publisher, year, edition, pages
2002.
Keyword [sv]
Markov lokalisering
Identifiers
URN: urn:nbn:se:hh:diva-10426Local ID: U5308OAI: oai:DiVA.org:hh-10426DiVA: diva2:365545
Uppsok
Technology
Note
Denna uppsats kan beställas från arkivet / This paper can be ordered from the archive. Kontakta / Contact: arkivet@hh.seAvailable from: 2010-11-09 Created: 2010-11-09Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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