In this dissertation, the mapping of outdoor environments and localization of a mobile robot in that setting is considered. It is well known that in the absence of a map or precise pose estimates, localization and mapping is a coupled problem. However, in this dissertation this problem is decoupled in to two disjoint steps / mapping and localization on the acquired map. First the images of the outdoor environment is downloaded from a website such as Google Earth and then these images are processed by utilizing several artificial neural
network topologies to create maps. Once these maps are obtained, the localization is done by using Monte Carlo localization.
This dissertation addresses a solution for the information which is most of the time taken for granted in most studies / a prior map of environment. Mapping is solved by using a novel approach / the map of the environment is created by
processing satellite images. Several global localization techniques are developed and evaluated to be used with these map so as to localize a mobile robot globally.
The outcome of this novel approach presented here may serve as a virtual GPS. Mobile phone applications can localize a user within a circle of uncertainty without GPS. This crude localization may be used to download relevant satellite images of the local environment. Once the mobile robot is localized on
the map created from the satellite images by using available techniques in the literature i.e. Monte Carlo localization, it may be claimed that it is localized on Earth.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610446/index.pdf |
| Date | 01 February 2009 |
| Creators | Dogruer, Can Ulas |
| Contributors | Koku, Ahmet Bugra |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | Ph.D. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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