Map Building Fusing Acoustic and Visual Information using Autonomous Underwater Vehicles

We present a system for automatically building 3-D maps of underwater terrain fusing visual data from a single camera with range data from multibeam sonar. The six-degree of freedom location of the camera relative to the navigation frame is derived as part of the mapping process, as are the attitude offsets of the multibeam head and the on-board velocity sensor. The system uses pose graph optimization and the square root information smoothing and mapping framework to simultaneously solve for the robot’s trajectory, the map, and the camera location in the robot’s frame. Matched visual features are treated within the pose graph as images of 3-D landmarks, while multibeam bathymetry submap matches are used to impose relative pose constraints linking robot poses from distinct tracklines of the dive trajectory. The navigation and mapping system presented works under a variety of deployment scenarios, on robots with diverse sensor suites. Results of using the system to map the structure and appearance of a section of coral reef are presented using data acquired by the Seabed autonomous underwater vehicle.