SLAM in Underwater Environment Using SIFT and Topologic Maps

The use of autonomous underwater vehicles (AUVs) for visual inspection tasks is a promising robotic field. The images captured by the robots can also aid in their localization/navigation. In this context, this paper proposes an approach to localization and mapping problem of underwater vehicle. Supposing the use of inspection cameras, this proposal is composed of two stages: i) the use of computer vision through the algorithm SIFT to extract the features in underwater image sequences and ii) the development of topological maps to localization and navigation. The integration of such systems will allow simultaneous localization and mapping of the environment. A set of tests with real robots was accomplished, regarding online and performance issues. The results reveals an accuracy and robust approach to several underwater conditions, as illumination and noise, leading to a promissory and original SLAM technique.