Robust vision-based underwater homing using self-similar landmarks
Negre, Amaury, Pradalier, Cedric, & Dunbabin, Matthew (2008) Robust vision-based underwater homing using self-similar landmarks. Journal of Field Robotics, 25(6/7), pp. 360-377.
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 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 the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions.
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|Item Type:||Journal Article|
|Keywords:||Self-similar landmarks, Autonomous underwater vehicles, Target tracking|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||21 Oct 2013 22:25|
|Last Modified:||28 Oct 2013 04:14|
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