Over the last 10 years, significant scientific effort has been dedicated to 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 paper summarizes our hardware, software, and experimental contributions on surface reconstruction over the last few years (2008)(2009)(2010)(2011). We propose the use of off-the-shelf sensors and a robotic platform to scan marine structures both above and below the waterline, and we develop a method and software system that uses the Ball Pivoting Algorithm (BPA) and the Poisson reconstruction algorithm to reconstruct 3-D surface models of marine structures from the scanned data. We have tested our hardware and software systems extensively in Singapore waters, including operating in rough waters, where water currents are around 1m/s to 2m/s. We present results on construction of various 3-D models of marine structures, including slowly moving structures such as floating platforms, moving boats and stationary jetties. Furthermore, the proposed surface reconstruction algorithm makes no use of any navigation sensor such as GPS, DVL or INS.

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Ahstract-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.

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