Markov lokalisering 2002 (Svenska)Självständigt arbete på grundnivå (kandidatexamen)Studentuppsats (Examensarbete)

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.

Ort, förlag, år, upplaga, sidor

2002.

Nyckelord [sv]

Markov lokalisering

Identifikatorer

URN: urn:nbn:se:hh:diva-10426Lokalt ID: U5308OAI: oai:DiVA.org:hh-10426DiVA, id: diva2:365545

Uppsök

teknik

Anmärkning

Denna uppsats kan beställas från arkivet / This paper can be ordered from the archive. Kontakta / Contact: arkivet@hh.seTillgänglig från: 2010-11-09 Skapad: 2010-11-09Bibliografiskt granskad

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Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE)

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