Accurate and detailed 3-dimensional (3D) models of the underwater environment are becoming increasingly important in modern marine surveys, since they convey immense information that can be easily interpreted. Techniques such as bundle adjustment (BA) and structure from motion (SfM), which jointly estimate sparse 3D points of the scene and camera poses, have gained popularity in underwater mapping applications. However, for large-area surveys these methods are computationally expensive and not intended for online application. This paper proposes an SfM pipeline based on solving the BA problem in an incremental and efficient way. Furthermore, the new system can provide not only the solution of the optimization (camera trajectory along time and the 3D points of the environment), but also the estimate of the uncertainty associated with the 3D reconstruction. This system is able to produce results in mission-time, i.e. while the robot is in the water or very shortly afterwards. Such quick availability is of great importance during survey operations as it allows data quality assessment in-situ, and eventual replanning of missions in case of need.
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