Robust vision-based underwater homing using self-similar landmarks

10 years 4 months ago
Robust vision-based underwater homing using self-similar landmarks
Next generation Autonomous Underwater Vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods, however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on Self-Similar Landmarks (SSL) that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that system performs exceptionally on limited processing power and demonstrates how the combined vision and controller systems enables robust target identification and docking in a variety of operating conditions.
Amaury Nègre, Cédric Pradalier, Matt
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JFR
Authors Amaury Nègre, Cédric Pradalier, Matthew Dunbabin
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