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Conference papers
Robust Vision-based Underwater Target Identification & Homing Using Self-Similar Landmarks
Abstract : Next generation Autonomous Underwater Vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localisation 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.
Cited literature [8 references]
https://hal.inria.fr/inria-00211881
Contributor : Amaury Nègre <>
Submitted on : Tuesday, January 22, 2008 - 10:33:00 AM
Last modification on : Thursday, November 19, 2020 - 1:00:20 PM
Long-term archiving on: : Thursday, April 15, 2010 - 1:56:52 AM
Contributor : Amaury Nègre <>
Submitted on : Tuesday, January 22, 2008 - 10:33:00 AM
Last modification on : Thursday, November 19, 2020 - 1:00:20 PM
Long-term archiving on: : Thursday, April 15, 2010 - 1:56:52 AM
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SSL_SB_FSR07.pdf
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