Autonomous Navigation for Unmanned Underwater Vehicles: Real-Time Experiments Using Computer Vision

This letter studies the problem of autonomous navigation for unmanned underwater vehicles, using computer vision for localization. Parallel tracking and mapping is employed to localize the vehicle with respect to a visual map, using a single camera, whereas an extended Kalman filter (EKF) is used to fuse the visual information with data from an inertial measurement unit, in order to recover the scale of the map and improve the pose estimation. A...