The localization of autonomous ground vehicles in dense urban environments poses a challenge.
Applications in classical outdoor robotics rely on the availability of GPS
systems in order to estimate the position. However, the presence of complex building structures in dense urban environments hampers a reliable localization based on GPS. Alternative approaches have to be applied In order to tackle this problem.
This thesis proposes an approach which combines observations of a single perspective camera and odometry in a probabilistic framework. In particular, the localization in the space of appearance is addressed. First, a topological map of reference places in the environment is built. Each reference place is associated with a set of visual features.
A feature selection is carried out in order to obtain distinctive reference
places. The topological map is extended to a hybrid representation by the use of metric information from Geographic Information Systems (GIS) and satellite images.
The localization is solved in terms of the recognition of reference places. A particle lter implementation incorporating this and the vehicle's odometry is presented.
The proposed system is evaluated based on multiple experiments in exemplary urban environments characterized by high building structures and a multitude of dynamic objects.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:23267 |
| Date | 25 January 2011 |
| Creators | Himstedt, Marian |
| Contributors | Böhme, Hans-Joachim, Alempijevic, Alen, Hochschule für Technik und Wirtschaft Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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