Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles
Data(s) |
2008
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Resumo |
This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed |
Formato |
application/pdf |
Identificador |
Salvi, J., Petillot, Y., i Batlle, E. (2008). Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles. IEEE/RSJ International Conference on Intelligent Robots and Systems : 2008 : IROS 2008, 1011-1016. Recuperat 04 juny 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4650627 978-1-4244-2057-5 |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
Reproducció digital del document publicat a: http://dx.doi.org/10.1109/IROS.2008.4650627 © IEEE/RSJ International Conference on Intelligent Robots and Systems : 2008 : IROS 2008, 2008, p. 1011-1016 Articles publicats (D-ATC) |
Direitos |
Tots els drets reservats |
Palavras-Chave | #Imatges -- Processament #Kalman, Filtre de #Robots mòbils #Robots submarins #Vehicles submergibles #Image processing #Kalman filtering G #Mobile robots #Submersibles #Underwater robots |
Tipo |
info:eu-repo/semantics/article |