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...

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Bibliographic Details
Main Authors: Garcia, R., Puig, J., Ridao, P., Cufi, X.
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Filtering
Image processing
Imatges
Kalman filtering G
Kalman filters
Kalman, Filtre de
Mobile robots
Motion estimation
Navigation
Oceans
Processament
Remotely operated vehicles
Robots mòbils
Robots submarins
Sea floor
State estimation
Underwater robots
Underwater vehicles
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Description
Summary: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.
DOI:10.1109/ROBOT.2002.1014362