Skip to main content

A Feature Based Navigation System for an Autonomous Underwater Robot

  • Chapter
Field and Service Robotics

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 42))

Summary

We present a system for autonomous underwater navigation as implemented on a Nekton Ranger autonomous underwater vehicle, AUV. This is one of the first implementations of a practical application for simultaneous localization and mapping on an AUV. Besides being an application of real-time SLAM, the implemtation demonstrates a novel data fusion solution where data from 7 sources are fused at different time scales in 5 separate estimators. By modularizing the data fusion problem in this way each estimator can be tuned separately to provide output useful to the end goal of localizing the AUV, on an a priori map. The Ranger AUV is equipped with a BlueView blazed array sonar which is used to detect features in the underwater environment. Underwater testing results are presented. The features in these tests are deployed radar reflectors.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 239.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dissanayake, M.G., Newman, P., et al.: A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans. on Robotics and Automation 17(3), 229–241 (2001)

    Article  Google Scholar 

  2. Newman, P., Leonard, J., Rikoski, R.: Towards constant-time slam on an autonomous underwater vehicle using synthetic aperture sonar. In: Proc. of the International Symposyum on Robotics Research (ISRR 2003) (2003)

    Google Scholar 

  3. Leonard, J., Rikoski, R., Newman, p., Bosse, M.: Mapping partially observable features from multiple uncertain vantage points. IJRR International Journal on Robotics Research 7(3), 943–975 (2002)

    Article  Google Scholar 

  4. Leonard, J.J., Rikoski, R.J.: Incorporation of delayed decision making into stochastic mapping. In: Experimental Robotics VII. lecture Notes in Control and Information Sciences, vol. 271, pp. 533–542. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  5. Ribas, D., Ridao, P., Neira, J., Tardos, J.: Slam using an imaging sonar for partially structured underwater environments. In: Proc. of the IEEE International Conference on Intelligent Robots and Systems(IROS 2006), IEEE, Los Alamitos (2006)

    Google Scholar 

  6. Leonard, J.J., Carpenter, R., Feder, H.J.S.: Stochastic mapping using forward look sonar. Robotica 19, 467–480 (2001)

    Article  Google Scholar 

  7. Tena, I., de Raucourt, S., Petillot, Y., Lane, D.: Concurrent mapping and localization using sidescan sonar. IEEE Journal of Ocean Engineering 29(2), 442–456 (2004)

    Article  Google Scholar 

  8. Castellanos, J.A., Neira, J., Tardós, J.D.: Multisensor fusion for simultaneous localization and map building. IEEE Transactions on Robotics and Automation 17(6), 908–914 (2001)

    Article  Google Scholar 

  9. Durrant-Whyte, H.F., Rao, B.Y.S., Hu, H.: Toward a fully decentralized architecture for multisensor datafusion. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA 1990) (1990)

    Google Scholar 

  10. Moutarlier, P., Chatila, R.: Stochastic multisensory data fusion for mobile robot location and environmental modelling. In: Proc. of the International Symposium on Robotics Research, pp. 85–94 (1990)

    Google Scholar 

  11. Guivant, J.E., Masson, F.: Using absolute non-Gaussian non-white observations in Gaussian SLAM. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA 2005), vol. 1, pp. 338–343 (2005)

    Google Scholar 

  12. Sukkarieh, S., Nebot, E., Durrant-Whyte, H., Corba, M.: A high integrity IMU/GPS navigation loop for autonomous land vehicle applications. IEEE Trans. on Robotics and Automation 15(3), 572–578 (1999)

    Article  Google Scholar 

  13. Dellaert, F.: Square root sam: Simultaneous location and mapping via square root information smoothing. In: Robotics: Science and Systems (2005)

    Google Scholar 

  14. Neira, J., Tardós, J.D.: Data association in stocastic mapping using the joint compatibility test. IEEE Transaction on Robotics and Automation 17(6), 890–897 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Christian Laugier Roland Siegwart

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Folkesson, J., Leederkerken, J., Williams, R., Patrikalakis, A., Leonard, J. (2008). A Feature Based Navigation System for an Autonomous Underwater Robot. In: Laugier, C., Siegwart, R. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75404-6_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-75404-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75403-9

  • Online ISBN: 978-3-540-75404-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics