Large scale egomotion and error analysis with visual features

• Autores: Miguel Cazorla Quevedo , Diego Viejo Hernando , Andres Hernandez-Gutierrez, Juan Nieto, Eduardo Nebot
• Localización: JoPha: Journal of Physical Agents, ISSN-e 1888-0258, Vol. 4, Nº. 1, 2010 (Ejemplar dedicado a: Special Session on Workshop of Physical Agents 2009), págs. 19-24
• Idioma: inglés
• DOI: 10.14198/jopha.2010.4.1.04
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• Resumen

  • Several works deal with 3D data in SLAM problem but many of them are focused on short scale maps. In this paper, we propose a method that can be used for computing the 6DoF trajectory performed by a robot from the stereo images captured during a large scale trajectory. The method transforms robust 2D features extracted from the reference stereo images to the 3D space. These 3D features are then used for obtaining the correct robot movement. Both Sift and Surf methods for feature extraction have been used. Also, a comparison between our method and the results of the ICP algorithm have been performed. We have also made a study about errors in stereo cameras.

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