Localization of AUV Using Visual Shape Information of Underwater Structures

수중 구조물 형상의 영상 정보를 이용한 수중로봇 위치인식 기법

Jung, Jongdae;Choi, Suyoung;Choi, Hyun-Taek;Myung, Hyun

  • Received : 2015.07.16
  • Accepted : 2015.10.22
  • Published : 2015.10.31


An autonomous underwater vehicle (AUV) can perform flexible operations even in complex underwater environments because of its autonomy. Localization is one of the key components of this autonomous navigation. Because the inertial navigation system of an AUV suffers from drift, observing fixed objects in an inertial reference system can enhance the localization performance. In this paper, we propose a method of AUV localization using visual measurements of underwater structures. A camera measurement model that emulates the camera’s observations of underwater structures is designed in a particle filtering framework. Then, the particle weight is updated based on the extracted visual information of the underwater structures. The proposed method is validated based on the results of experiments performed in a structured basin environment.


Autonomous navigation;Localization;Vision;Underwater structures;Particle filter


  1. Kondo, H., Ura, T., Nose, Y., Akizono, J., Sakai, H., 2003. Visual Investigation of Underwater Structgures by the AUV and Sea Trials. Proceedings of OCEANS, 1, 340-345.
  2. Lee, D., Kim, G., Kim, D., Myung, H., Choi, H.-T., 2012. Vision-based Object Detection and Tracking for Autonomous Navigation of Underwater Robots. Ocean Engineering, 48, 59-68.
  3. Li, J., Lee, M., Kim, J.-G., Kim, J.-T., Suh, J., 2014. Development of P-SURO II Hybrid AUV and Its Experimental Study. Proceedings of MTS/IEEE OCEANS, Bergen, 1-6.
  4. Meyer, F., Beucher, S., 1990. Morphological Segmentation. Journal of Visual Communication and Image Representation, 1(1) 21-46.
  5. Paull, L, 2014. AUV Navigation and Localization: A Review. IEEE Oceanic Engineering, 93(1), 131-149.
  6. Thrun, S., Burgard, W., Fox, D., 2005. Probabilistic Robotics. MIT Press, Cambridge.
  7. Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P.S.,üSstrunk, S., 2012. SLIC Superpixels Compared to State-of-the-art Superpixel Methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11), 2274-2282.
  8. Fernandez-Madrigeal, J., Claraco, J.L., 2013. Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods. Information Science Reference, Hershey, PA.
  9. Kim, D., Lee, D., Myung, H., Choi, H.-T., 2014. Artificial Landmark-based Underwater Localization for AUV Using Weighted Template Matching. Journal of Intelligent Service Robots, 7(3), 175-184.
  10. Kondo, H., Maki, T., Ura, T., Nose, Y., Sakamaki, T., Inaishi, M., 2004. Relative Navigation of an Autonomous Underwater Vehicle Using a Light-section Profiling System. Proceedings of IEEE International Conference on Intelligent Robots and Systems, 1103-1108.