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Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

IEEE

Author: García Campos, Rafael
Puig, Jordi
Ridao Rodríguez, Pere
Cufí i Solé, Xavier
Abstract: Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position
Document access: http://hdl.handle.net/2072/59097
Language: eng
Publisher: IEEE
Rights: Tots els drets reservats
Subject: Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
Title: Augmented state Kalman filtering for AUV navigation
Type: info:eu-repo/semantics/article
Repository: Recercat

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