The main focus of the study is the implementation of a practical indoor localization and
mapping algorithm for large scale, structured indoor environments. Building an incremental
consistent map while also using it for localization is partially unsolved problem and of prime
importance for mobile robot navigation. Within this framework, a combined method
consisting of feature based scan matching and FastSLAM algorithm using LADAR and
odometer sensor is presented. In this method, an improved data association and localization
accuracy is achieved by feeding the SLAM module with better incremental pose information
from scan matching instead of raw odometer output.
This thesis presents the following contributions for indoor localization and mapping. Firstly
a method combining feature based scan matching and FastSLAM is achieved. Secondly,
improved geometrical relations are used for scan matching and also a novel method based on
vector transformation is used for the calculation of pose difference. These are carefully
studied and tuned based on localization and mapping performance failures encountered in
different realistic LADAR datasets. Thirdly, in addition to position, orientation information
usage in line segment and corner oriented data association is presented as an extension in
FastSLAM module.
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The method is tested with LADAR and odometer data taken from real robot platforms
operated in different indoor environments. In addition to using datasets from the literature,
own datasets are collected on Pioneer 3AT experimental robot platform. As a result, a real
time working localization algorithm which is pretty successive in large scale, structured
environments is achieved.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612431/index.pdf |
| Date | 01 September 2010 |
| Creators | Ozgur, Ayhan |
| Contributors | Saranli, Afsar |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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