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@INPROCEEDINGS{Teclaw2015_MMAR,
  author = {Teclaw, M. and Lech, P. and Okarma, K.},
  title = {Simulation of the Visual Self-Localization of Mobile Robots Based
	on Image Similarity Metrics},
  booktitle = {Methods and Models in Automation and Robotics (MMAR), 2015 20th International
	Conference on},
  year = {2015},
  pages = {915-920},
  month = {Aug},
  publisher = {IEEE},
  abstract = {In the paper the idea of the visual self-localization of mobile robots
	based on the estimation of image similarity is discussed. It is assumed
	that a rough position of the mobile robot is known e.g. from the
	built-in GPS device. Assuming known orientation of the robot, the
	main advantage of the application of image analysis algorithms is
	the increase of the self-localization accuracy. The basic idea of
	our approach is related to the use of image similarity metrics for
	the estimation of the distance to the known positions associated
	with the images stored in the database. In order to verify the the
	validity of the proposed approach for the images containing textures
	characteristic for urban areas, some experiments have been conducted
	in Java based Simbad environment. As the result of applying various
	image similarity metrics for this purpose, the noticeable increase
	of the localization accuracy has been obtained for the artificial
	model of the urban area developed in Simbad environment. Nevertheless,
	achieved results are encouraging for further experiments utilizing
	natural images captured by real cameras also in the presence of various
	image distortions.},
  doi = {10.1109/MMAR.2015.7283999},
  url = {http://dx.doi.org/10.1109/MMAR.2015.7283999}
}