Underwater 3D Reconstruction for Underwater Construction Robot Based on 2D Multibeam Imaging Sonar

  • Song, Young-eun ;
  • Choi, Seung-Joon
  • Received : 2016.03.17
  • Accepted : 2016.06.24
  • Published : 2016.06.30


This paper presents an underwater structure 3D reconstruction method using a 2D multibeam imaging sonar. Compared with other underwater environmental recognition sensors, the 2D multibeam imaging sonar offers high resolution images in water with a high turbidity level by showing the reflection intensity data in real-time. With such advantages, almost all underwater applications, including ROVs, have applied this 2D multibeam imaging sonar. However, the elevation data are missing in sonar images, which causes difficulties with correctly understanding the underwater topography. To solve this problem, this paper concentrates on the physical relationship between the sonar image and the scene topography to find the elevation information. First, the modeling of the sonar reflection intensity data is studied using the distances and angles of the sonar beams and underwater objects. Second, the elevation data are determined based on parameters like the reflection intensity and shadow length. Then, the elevation information is applied to the 3D underwater reconstruction. This paper evaluates the presented real-time 3D reconstruction method using real underwater environments. Experimental results are shown to appraise the performance of the method. Additionally, with the utilization of ROVs, the contour and texture image mapping results from the obtained 3D reconstruction results are presented as applications.


Underwater topography;3D Reconstruction;ROV;2D Multibeam Imaging Sonar;Underwater Construction Robot


  1. Brandou, V., Allais, A.G., Perrier, M., Malis, E., Rives, P., Sarrazin, J., Sarradin, P.M., 2007. 3d Reconstruction of Natural Underwater Scenes using the Stereovision System Iris. Proceedings of IEEE OCEANS 2007-Europe, 1-6.
  2. Aykin, M., Negahdaripour, S., 2012. Forward-look 2-d Sonar Image Formation and 3d Reconstruction. Proceedings of IEEE/MTS Oceans 12 Conference.
  3. Beall, C., Lawrence, B.J., Ila, V., Dellaert, F., 2010. 3d Reconstruction of Underwater Structures. Proceedings of Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, 4418-4423.
  4. Coiras, E., Petillot, Y., Lane, D.M., 2007. Multiresolution 3-d Reconstruction from Side-scan Sonar Images. IEEE Transactions on Image Processing, 16(2), 382-390.
  5. Hansen, R., Andersen, P., 1996. A 3d Underwater Acoustic Camera Properties and Applications. Acoustical Imaging. Springer, 607-611.
  6. Hansen, R.K., Andersen, P.A., 1993. 3d Acoustic Camera for Underwater Imaging. Acoustical Imaging. Springer, 723-727.
  7. Massot-Campos, M., Oliver-Codina, G., 2014. Underwater Laser-based Structured Light System for One-shot 3d Reconstruction. Proceedings of Sensors 2014.
  8. Negahdaripour, S., Sarafraz, A., 2014. Improved Stereo Matching in Scattering Media by Incorporating Backscatter Cue.
  9. Papadopoulos, G., Kurniawati, H., Shariff, B.M., Shafeeq, A., Wong, L.J., Patrikalakis, N.M., 2011. 3d Surface Reconstruction for Partially Submerged Marine Structures using an Autonomous Surface Vehicle. Proceedings of Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on. IEEE, 3551-3557.
  10. Pizarro, O., Eustice, R., Singh, H., 2004. Large Area 3d Reconstructions from Underwater Surveys. OCEANS’04. MTTS/IEEE TECHNOOCEAN’04, 2, 678-687.
  11. Teledyne BlueView, 2015. BlueView P-900. [Online]. Available at: [Accessed 12 March. 2016].


Grant : 수중건설로봇사업단

Supported by : 한국해양과학기술원