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|Title:||3D-surface reconstruction for partially submerged marine structures using an autonomous surface vehicle||Authors:||Papadopoulos, G.
Bin Mohd Shariff, A.S.
|Issue Date:||2011||Citation:||Papadopoulos, G.,Kurniawati, H.,Bin Mohd Shariff, A.S.,Wong, L.J.,Patrikalakis, N.M. (2011). 3D-surface reconstruction for partially submerged marine structures using an autonomous surface vehicle. IEEE International Conference on Intelligent Robots and Systems : 3551-3557. ScholarBank@NUS Repository. https://doi.org/10.1109/IROS.2011.6048609||Abstract:||Over the last eight years, significant scientific effort has been dedicated on the problem of 3-D surface reconstruction for structural systems. However, the critical area of marine structures remains insufficiently studied. The research presented here focuses on the problem of 3-D surface reconstruction in the marine environment. This work is an extension of our previous approach, in which a surface vehicle that was equipped with a powerful laser scanner was designed and used to scan the above-water part of the marine structure of interest. Here we propose the design of a novel surface vehicle that is capable of using laser scanners and a side-looking sonar to scan marine structures both above and below the waterline. We also study the issue of downsampling the dataset in order to perform efficient surface reconstruction of the considered 3-D geometry, and we present a methodology for combining and integrating data from the above- and below-water parts of the structure. To illustrate the proposed robotic platform and validate our algorithms, we present results from a set of experiments in the Singapore Sea. Specifically, we present 2 different maps: the above-water map and the combined above-and below-water map. In both cases, we have two different maps: a lower quality map, that can be generated on-line, and a higher quality map that is generated off-line. To the best of our knowledge, our work is the only one that provides a 3-D model for both above- and below-water parts of marine structures. In this work we assumed a GPS-denied environment, without using any other navigation sensor such as DVL or INS. © 2011 IEEE.||Source Title:||IEEE International Conference on Intelligent Robots and Systems||URI:||http://scholarbank.nus.edu.sg/handle/10635/124982||ISBN:||9781612844541||DOI:||10.1109/IROS.2011.6048609|
|Appears in Collections:||Staff Publications|
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