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A plethora of state estimation techniques have appeared in the last decadeusing visual data, and more recently with added inertial data. Datasetstypically used for evaluation include indoor and urban environments, wheresupporting videos have shown impressive performance. However, such techniqueshave not been fully evaluated in challenging conditions, such as the marinedomain. In this paper, we compare ten recent open-source packages to provideinsights on their performance and guidelines on addressing current challenges.Specifically, we selected direct methods and tightly-coupled optimizationtechniques that fuse camera and Inertial Measurement Unit (IMU) data together.Experiments are conducted by testing all packages on datasets collected overthe years with underwater robots in our laboratory. All the datasets are madeavailable online.

Experimental Comparison of Open Source Visual-Inertial-Based State Estimation Algorithms in the Underwater Domain