Markov lokalisering 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.

Keywords [sv]

Markov lokalisering

Identifiers

URN: urn:nbn:se:hh:diva-10426Local ID: U5308OAI: oai:DiVA.org:hh-10426DiVA, id: 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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School of Information Science, Computer and Electrical Engineering (IDE)

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