Skip to main content

Path Planning for the Autonomous Underwater Vehicle

  • Conference paper
Swarm, Evolutionary, and Memetic Computing (SEMCCO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8298))

Included in the following conference series:


This paper introduces a novel method to find the optimal path for Autonomous Underwater Vehicles (AUVs). AUVs have gained importance over the last few years as service and research tools in a variety of applications. Path planning is one of the challenging tasks when dynamic obstacles are encountered. The Dijkstra’s algorithm is modified suitably to account for static as well as dynamic obstacles by adding an Additional Part (AP). In addition, the proposed algorithm takes into account the dynamics of the water flow and corrects the path suitably. Only two-dimensional routes are considered in the applications. The numerical results show that the proposed algorithm is effective in finding optimal paths.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others


  1. Yuh, J.: Design and Control of Autonomous Underwater Robots: A Survey. Kluwer Academic Publisher, Netherlands (2000)

    Google Scholar 

  2. Griffiths, G.: Technology and Applications of Autonomous Underwater Vehicles. Taylor & Francis Inc., UK (2003)

    Google Scholar 

  3. Zilouchian, A.: Intelligent Control Systems Using Soft Computing Methodologies. CRC Press, USA (2000)

    Google Scholar 

  4. Merrigan, M.: A Refinement to the World Geodetic System 1984 Reference Frame, pp. 2–4. Institute of Navigation (2002)

    Google Scholar 

  5. Kirsanov, M.: Practical Programming in Maple. MPEI Publisher, Russia (2011)

    Google Scholar 

  6. Kirsanov, M.: Graphs in Maple. Fizmatlit Press, Russia (2007)

    Google Scholar 

  7. Lin, M., Canny, J.: A Fast Algorithm for Incremental Distance Calculation. In: Proceedings of IEEE Int. Conf. Robotics and Automation, US, pp. 1008–1014 (1991)

    Google Scholar 

  8. Jones, T.: Al Application Programming. harles River Media Programming, US (2005)

    Google Scholar 

  9. Lillesand, T.: Remote sensing and image interpretation. University of Wisconsin-Madison Publisher, US (2004)

    Google Scholar 

  10. Fujii, T.: Laser Remote Sensing. CRC Press, US (2005)

    Google Scholar 

  11. Braunl, T.: Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems. Springer, Australia (2008)

    Book  Google Scholar 

  12. Guohua, X.: Second International Conference on Intelligent Robotics and Applications, ICIRA, Singapore, pp. 1138–1145 (2009)

    Google Scholar 

  13. Russell, J.: Realflow, Book on Demand, US (2012)

    Google Scholar 

  14. Jiyuan, T.: Computational Fluid Dynamics: A Practical Approach, UK (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Kirsanov, A., Anavatti, S.G., Ray, T. (2013). Path Planning for the Autonomous Underwater Vehicle. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8298. Springer, Cham.

Download citation

  • DOI:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03755-4

  • Online ISBN: 978-3-319-03756-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics