Skip to main content

Determination of the Relative Position of Space Vehicles by Detection and Tracking of Natural Visual Features with the Existing TV-Cameras

  • Conference paper
  • First Online:

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 542))

Abstract

During spacecrafts maneuvers, especially at the rendezvous and docking stages, one of the most important tasks is to determine the relative positions of the vehicles. The current Russian “Course” and recently proposed ATV/HTV docking systems are complex and require mounting of specific cumbersome equipment on the outer sides of both vehicles. The proposed TV-based docking control system uses the existing cameras, “natural” visible features of the ISS and an ISS laptop to determine all six relative coordinates of the vehicles. At the training stage the ISS 3D-model and video recordings are used. This paper describes the algorithm flow and the problems of the passive, TV-only approach. The system efficiency is tested against models, mockups and the recordings of previous rendezvous of “Progress”, “Soyuz” and ATV spacecrafts. The nearest goal of the system is to become an independent docking control system helping the ground docking control team and the cosmonauts.

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   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

References

  1. Bakhshiev, A.V., Stepanov, D.N., et al.: Proposals development for the design and technical implementation of the determining parameters relative motion system based by video processing. Technical report. Saint-Petersburg, Russia, RTC, 143 (2010)

    Google Scholar 

  2. Moreno-Noguer, F., Lepetit, Y., Fua, P.: Accurate noniterative o(n) solution to the PnP problem. In: de Janeiro, R. (ed.) Proceeding of the IEEE International Conference on Computer Vision, Brazil, October 2007

    Google Scholar 

  3. Gao, X.S., Hou, X.R.: Complete solution classification for the perspective-three-point problem. IEEE Trans. Pattern Anal. Mach. Intell. 25, 930–934 (2003)

    Article  Google Scholar 

  4. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  5. Bouguet, J.Y.: MATLAB calibration tool. http://www.vision.caltech.edu/bouguetj/calib_doc

  6. Tsai, R.Y.: A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE J. Robot. Autom. RA–3(4), 323–344 (1987)

    Article  Google Scholar 

  7. Horn, B.K.P.: Tsai’s Camera Calibration method Revisited. MIT Press, McGraw-Hill, Cambridge, New York (2000)

    Google Scholar 

  8. Liao, S., Zhu, X., Lei, Z., Zhang, L., Li, S.Z.: Learning multi-scale block local binary patterns for face recognition. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 828–837. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Viola, P., Jones, M.J.: Rapid object detection using a boosted cascade of simple features. Comput. Vis. Pattern Recogn. 1, 511–518 (2001)

    Google Scholar 

  10. Freund, Y., Schapire, R.E.: A short introduction to boosting. In: International Joint Conference on Artificial Intelligence, vol. 2, pp. 1401–1406 (1999)

    Google Scholar 

  11. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57, 137–154 (2004)

    Article  Google Scholar 

  12. Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34, 1409–1422 (2012)

    Article  Google Scholar 

  13. Bakhshiev, A.V., Korban, P.A., Kirpan, N.A.: Software package for determining the spatial orientation of objects by tv picture in the problem space docking. Robot. Tech. Cybern., Saint-Petersburg, Russ., RTC 1, 71–75 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dmitrii Stepanov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Stepanov, D., Bakhshiev, A., Gromoshinskii, D., Kirpan, N., Gundelakh, F. (2015). Determination of the Relative Position of Space Vehicles by Detection and Tracking of Natural Visual Features with the Existing TV-Cameras. In: Khachay, M., Konstantinova, N., Panchenko, A., Ignatov, D., Labunets, V. (eds) Analysis of Images, Social Networks and Texts. AIST 2015. Communications in Computer and Information Science, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-319-26123-2_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-26123-2_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26122-5

  • Online ISBN: 978-3-319-26123-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics