Skip to main content

Biologically Inspired Path Execution Using SURF Flow in Robot Navigation

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6692))

Abstract

An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Trucco, E., Verri, A.: Introductory Techniques for 3-D Computer Vision. Prentice Hall PTR, Upper Saddle River (1998)

    Google Scholar 

  2. Giachetti, A., Campani, M., Torre, V.: The Use of Optical Flow for Road Navigation. IEEE Trans. on Robotics and Automation 14, 34–48 (1998)

    Google Scholar 

  3. Dev, A., Krose, B., Groen, F.: Navigation of a mobile robot on the temporal development of the optic flow. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 558–563 (1997)

    Google Scholar 

  4. Nagatani, K., Tachibana, S., Sofne, M., Tanaka, Y.: Improvement of odometry for omnidirectional vehicle using optical flow information. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1, pp. 468–473 (2000)

    Google Scholar 

  5. Sorensen, D.K., Smukala, V., Ovinis, M., Lee, S.: On-line optical flow feedback for mobile robot localization/navigation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 1246–1251 (2003)

    Google Scholar 

  6. Nelson, R.C., Aloimonos, J.: Obstacle avoidance using flow field divergence. Trans. on Pattern Analysis and Machine Intelligence 11, 1102–1106 (2002)

    Google Scholar 

  7. Srinivasan, M., Chahl, J., Weber, K., Venkatesh, S., Nagle, M., Zhang, S.: Robot navigation inspired by principles of insect vision. Robotics and Autonomous Systems 26, 203–216 (1999)

    Google Scholar 

  8. Duchon, A.P., Warren, W.H.: Robot navigation from a Gibsonian viewpoint. In: IEEE International Conference on Systems, Man, and Cybernetics, ‘Humans, Information and Technology’, vol. 3, pp. 2272–2277 (1994)

    Google Scholar 

  9. Warren, W.H., Kay, B.A., Zosh, W.D., Duchon, A.P., Sahuc, S.: Optic flow is used to control human walking. Nature Neuroscience 4, 213–216 (2001)

    Google Scholar 

  10. Warren, W.H., Hannon, D.J.: Direction of self-motion is perceived from optical flow. Nature 336, 162–163 (1988)

    Google Scholar 

  11. Santos-Victor, J., Sandini, G., Curotto, F., Garibaldi, S.: Divergent stereo in autonomous navigation: From bees to robots. International Journal of Computer Vision 14, 159–177 (1995)

    Google Scholar 

  12. Thompson, W.B., Kearney, J.K.: Inexact Vision. In: Proc. Workshop on Motion: Representation and Analysis, pp. 15–22 (1986)

    Google Scholar 

  13. Negahdaripour, S., Horn, B.K.P.: A Direct Method for Locating the Focus of Expansion. Computer Vision, Graphics, and Image Processing 46, 303–326 (1989)

    Google Scholar 

  14. Branca, A., Stella, E., Attolico, G., Distante, A.: Focus of Expansion estimation by an error backpropagation neural network. Neural Computing & Applications 6, 142–147 (1997)

    Google Scholar 

  15. Yoon, K., Jang, G., Kim, S., Kweon, I.: Color landmark based self-localization for indoor mobile robots. J. Control Autom. Syst. Eng. 7(9), 749–757 (2001)

    Google Scholar 

  16. Deng, X., Milios, E., Mirzaian, A.: Landmark selection strategies for path execution. Robotics and Autonomous Systems 17, 171–185 (1996)

    Google Scholar 

  17. Herbert, B., Tinne, T., Luc, V.: Surf: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)

    Google Scholar 

  18. Lowe, D.G.: Object recognition from local scale-invariant features. In: IEEE International Conference on Computer Vision, USA, vol. 2, p. 1150 (1999)

    Google Scholar 

  19. Liu, C., Yuen, J., Torralba, A., Sivic, J., Freeman, W.: SIFT flow: dense correspondence across different scenes. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 28–42. Springer, Heidelberg (2008)

    Google Scholar 

  20. Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: IJCAI, vol. 3, pp. 674–679. Citeseer (1981)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Perez-Sala, X., Angulo, C., Escalera, S. (2011). Biologically Inspired Path Execution Using SURF Flow in Robot Navigation. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_73

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21498-1_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21497-4

  • Online ISBN: 978-3-642-21498-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics