Skip to main content
Log in

Simultaneous localization and mapping of autonomous underwater vehicle using looking forward sonar

Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Cite this article


A method of underwater simultaneous localization and mapping (SLAM) based on on-board looking forward sonar is proposed. The real-time data flow is obtained to form the underwater acoustic images and these images are pre-processed and positions of objects are extracted for SLAM. Extended Kalman filter (EKF) is selected as the kernel approach to enable the underwater vehicle to construct a feature map, and the EKF can locate the underwater vehicle through the map. In order to improve the association efficiency, a novel association method based on ant colony algorithm is introduced. Results obtained on simulation data and real acoustic vision data in tank are displayed and discussed. The proposed method maintains better association efficiency and reduces navigation error, and is effective and feasible.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others


  1. Anderson B, Crowell J. Workhorse AUV: A cost-sensible new autonomous underwater vehicle for surveys/soundings, search & rescue, and research [C]//Proceedings of MTS/IEEE OCEANS 2005. Washington DC: IEEE, 2005: 1228–1233.

    Google Scholar 

  2. Grasmueck M, Eberli G P, Viggiano D A, et al. Autonomous underwater vehicle (AUV) mapping reveals coral mound distribution, morphology, and oceanography in deep water of the Straits of Florida [J]. Geophysical Research Letters, 2006, 33(23): 616–622.

    Article  Google Scholar 

  3. Kinsey J C, Eustice R M, Whitcomb L L. A survey of underwater vehicle navigation: Recent advances and new challenges [C]//Proceedings of the 7th IFAC Conference on Manoeuvring and Control of Marine Craft. Lisbon, Portugal: IFAC, 2006: 435–445.

    Google Scholar 

  4. Williams S B, Newman P, Dissanayake G, et al. Autonomous underwater simultaneous localization and map building [C]//IEEE International Conference on Robotics & Automation. San Francisco, CA: IEEE, 2000: 1793–1798.

    Google Scholar 

  5. Eustice R M, Whitcomb L L, Singh H, et al. Experimental results in synchronous-clock one-way-travel-time acoustic navigation for autonomous underwater vehicles [C]//IEEE International Conference on Robotics and Automation. Rome, Italy: IEEE, 2007: 4257–4264.

    Google Scholar 

  6. Durrant-Whyte H, Bailey T. Simultaneous localization and mapping. Part I [J]. IEEE Robotics & Automation Magazine, 2006, 13(2): 99–108.

    Article  Google Scholar 

  7. Mahon I, Williams S. SLAM using natural features in an underwater environment [C]// Proceedings of 8th International Conference on Control, Automation, Robotics and Vision. Kunming, China: IEEE, 2004: 2076–2081.

    Google Scholar 

  8. Bailey T. Mobile robot localization and mapping in extensive outdoor environments [D]. Sydney: Australian Centre for Field Robotics, University of Sydney, 2002.

    Google Scholar 

  9. Folkesson J, Leonard J, Leederkerken J, et al. Feature tracking for underwater navigation using sonar [C]//Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. San Diego, CA: IEEE, 2007: 3678–3684.

    Chapter  Google Scholar 

  10. Zhang Tie-dong, Wan Lei, Ma Yue. A preprocess method of the looking forward sonar image [J]. Acoustics and Electronics Engineering, 2008 (91): 14–18 (in Chinese).

  11. David R. Towards simultaneous localization & mapping for an AUV using an imaging sonar [D]. Girona: Department of Electronics, Informatics and Automation, University of Girona, 2005.

    Google Scholar 

  12. Tardós J D, Neira J, Newman P M, et al. Robust mapping and localization in indoor environments using sonar data [J]. International Journal of Robotics Research, 2002, 21(4): 311–330.

    Article  Google Scholar 

  13. Cooper A J. A comparison of data association techniques for simultaneous localization and mapping [D]. Boston: Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 2005.

    Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Wen-jing Zeng  (曾文静).

Additional information

Foundation item: the National Natural Science Foundation of China (No. 51009040), the Fund of National Defence Key Laboratory of Autonomous Underwater Vehicle Technology (No. 2008002), and the Scientific Service Special Fund of University in China (No. E091002)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Zeng, Wj., Wan, L., Zhang, Td. et al. Simultaneous localization and mapping of autonomous underwater vehicle using looking forward sonar. J. Shanghai Jiaotong Univ. (Sci.) 17, 91–97 (2012).

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI:

Key words

CLC number