Large scale egomotion and error analysis with visual features

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Title: Large scale egomotion and error analysis with visual features
Authors: Cazorla, Miguel | Viejo Hernando, Diego | Hernández Gutiérrez, Andrés | Nieto, Juan | Nebot, Eduardo
Research Group/s: Robot Vision Group
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Computer vision | Mobile robotics
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: Jan-2010
Publisher: Red de Agentes Físicos
Citation: CAZORLA, M., et al. “Large scale egomotion and error analysis with visual features”. Journal of Physical Agents. Vol. 4, No. 1 (Jan. 2010). ISSN 1888-0258, pp. 19-24
Abstract: 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.
Sponsor: This work has been supported by grant JC08-00077 from Ministerio de Ciencia e Innovación of the Spanish Government.
URI: |
ISSN: 1888-0258
DOI: 10.14198/JoPha.2010.4.1.04
Language: eng
Type: info:eu-repo/semantics/article
Peer Review: si
Appears in Collections:Journal of Physical Agents - 2010, Vol. 4, No. 1
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