Feature-Based Stereo Vision for Ship-Deck Landing

doi:10.4050/F-0081-2025-0213

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Feature-Based Stereo Vision for Ship-Deck Landing

Victoria Britcher, Anubhav Datta, Inderjit Chopra, University of Maryland

https://doi.org/10.4050/F-0081-2025-0213

Abstract:
In this paper, we develop a new feature-based algorithm using stereo cameras to estimate stochastic ship-deck motion at high sea states. Unlike our previous algorithms, this algorithm is able to estimate the motion of arbitrary ship structures without prior information on the ship's visual appearance or geometry. The algorithm requires an initial pose and suffers from drift over time, which was resolved by fusing it with our previous 2D feature-based vision algorithm. The combined vision algorithm is validated using a simulated ship featuring 3D ship structures and 2D flight deck markings representative of a DDG-51 ship. The results indicate that the algorithm can accurately estimate the pose of a simulated ship undergoing Sea-State 6 motion. The vision algorithm was further validated in a simple free-flight test.