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Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

IEEE

Autor: García Campos, Rafael
Nicosevici, Tudor
Ridao Rodríguez, Pere
Ribas Romagós, David
Resum: This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory
Accés al document: http://hdl.handle.net/2072/59096
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
Títol: Towards a real-time vision-based navigation system for a small-class UUV
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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