In this Master Thesis different approaches to mobile localization within construction environments are investigated. At first an overview of different sensors commonly used within localization is presented together with different map representations and a system consisting of a laser scanner and wheel encoders is chosen. The hardware is prepared for the open source ROS environment and three different algorithms for localization are tested. Two algorithms, Gmapping and HectorSLAM, used for Simultaneous Localization and Mapping, are compared. The best map is then used by a Monte Carlo localization algorithm, AMCL, for autonomous navigation. It is found that HectorSLAM produces the most accurate map, given that the grid refinement level is fine enough for the environment. It is also found that the maximum Kullback Leiber distance, used in AMCL, needs to be calibrated in order to perform a sufficient navigation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-326270 |
| Date | January 2017 |
| Creators | Pettersson, Rasmus |
| Publisher | Uppsala universitet, Fasta tillståndets elektronik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC F, 1401-5757 ; 17042 |
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