Skip to main content
SpringerLink
Log in

Tracking Extended Moving Objects with a Mobile Robot

  • Chapter
Intelligent Techniques and Tools for Novel System Architectures

Part of the book series: Studies in Computational Intelligence ((SCI,volume 109))

Summary

Tracking moving objects is of central interest in mobile robotics. It is a prerequisite for providing a robot with cooperative behaviour. Most algorithms assume punctiform targets, which is not always suitable. In this work we expand the problem to extended objects and compare the algorithms that have been developed by our research group. These algorithms are capable of tracking extended objects. It is shown that there are great differences between tracking robots, where a certain shape can be assumed, and people.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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. Bar-Shalom, Y., Fortmann, T.: Tracking and Data Association. Academic Press, New York (1988)

    MATH  Google Scholar 

  2. Prassler, E., Scholz, J., Elfes, E.: Tracking people in a railway station during rush-hour. Computer Vision Systems 1542 (1999) 162–179. Springer Lecture Notes

    Google Scholar 

  3. Schulz, D., Burgard, W., Fox, D., Cremers, A. B.: Tracking multiple moving objects with a mobile robot. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001)

    Google Scholar 

  4. Fod, A., Howard, A., Mataric, M. J.: Laser-based people tracking. IEEE International Conference on Robotics and Automation (ICRA 2002) 3024–3029

    Google Scholar 

  5. Fuerstenberg, K. C., Linzmeier, D. T., Dietmayer, K. C. J.: Pedestrian recognition and tracking of vehicles using a vehicle based multilayer laserscanner. Intelligent Vehicles Symposium 1 (2002) 31–35

    Google Scholar 

  6. Thrun, S.: Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence 99(1) (1998) 21–71

    Article  MATH  Google Scholar 

  7. Thrun, S., Fox, D., Burgard, W.: Markov localization for mobile robots in dynamic environments. Journal of Artificial Intelligence Research 11 (1999) 391–427

    MATH  Google Scholar 

  8. Streit, R. L., Luginbuhl, T. E.: Maximum Likelihood Method for Multi-Hypothesis Tracking. Signal and Data Processing of Small Targets 2335 (1994)

    Google Scholar 

  9. Quach, T., Farrooq, M.: Maximum Likelihood Track Formation with the Viterbi Algorithm. 33rd Conference on Decision and Control (1994)

    Google Scholar 

  10. Stannus, W., Koch, W., Kräußling, A.: On robot-borne extended object tracking using the EM algorithm. 5th Symposium on Intelligent Autonomous Vehicles, Lisbon, Portugal (IAV 2004)

    Google Scholar 

  11. Kräußling, A., Schneider, F. E., Wildermuth, D.: Tracking expanded objects using the Viterbi algorithm. IEEE Conference on Intelligent Systems, Varna, Bulgaria (IS 2004)

    Google Scholar 

  12. Kräußling, A., Schneider, F. E., Wildermuth, D.: Tracking of extended crossing objects using the Viterbi algorithm. 1st International Conference on Informatics in Control, Automation and Robotics, Setubal, Portugal (ICINCO 2004)

    Google Scholar 

  13. Kräußling, A., Schneider, F. E., Wildermuth, D.: A switching algorithm for tracking extended targets. 2nd International Conference on Informatics in Control, Automation and Robotics, Barcelona, Spain (ICINCO 2005), also to be published in the Springer book of best papers of ICINCO 2005

    Google Scholar 

  14. Kalman, R. E.: A new approach to linear filtering and prediction problems. Transaction of the ASME Journal of Basic Engineering 82 (1960) 34–45

    Google Scholar 

  15. Bar-Shalom, Y., Tse, E.: Tracking in a cluttered environment with probabilistic data association. Automatica 11 (1975) 451–460

    Article  MATH  Google Scholar 

  16. Dempster, A. P., Laird, N., Rubin, D. B.: Maximum likelihood from incomplete likelihood via the EM algorithm. Journal of the Royal Statistical Society B 39 (1977) 1–38

    MATH  MathSciNet  Google Scholar 

  17. Shumway, R. H., Stoffer, D. S.: Time series analysis and its applications. Springer, Berlin Heidelberg New York (2000)

    MATH  Google Scholar 

  18. Mahalanobis, P. C.: On the generalized distance in statistics. Proceedings of the National Institute of Science 12 (1936) 49–55

    Google Scholar 

  19. Bronstein, I. N., Semendjajew, K. A.: Taschenbuch der Mathematik. Verlag Harri Deutsch Thun und Frankfurt/Main (1987)

    Google Scholar 

  20. Zhao, H., Shibasaki, R.: A novel system for tracking pedestrians using multiple single-row laser-range scanners. IEEE Transactions on Systems Man and Cybernetics – Part A: Systems and Humans 35(2) (2005) 283–291

    Article  Google Scholar 

  21. Technical information sheet lms/lms 200/lms 211/ lms 29. Sick Inc. 6900 West 110th Street Minneapolis MN 55438

    Google Scholar 

  22. Kräußling, A.: A fast algorithm for tracking multiple interacting objects. Submitted to the 3rd European Conference on Mobile Robots (ECMR 2007)

    Google Scholar 

  23. Burgard, W., Fox, D., Hennig, D., Schmidt, T.: Estimating the absolute position of a mobile robot using position probability grids. Proc. of AAAI (1996)

    Google Scholar 

  24. Fox, D., Burgard, W., Thrun, S., Cremers, A., B.: Position estimation for mobile robots in dynamic environments. Proc. of AAAI (1998)

    Google Scholar 

  25. Fox, D., Burgard, W., Dellaert, F., Thrun, S.: Monte Carlo localization: effizient position estimation for mobile robots. Proc. of AAAI (1999)

    Google Scholar 

  26. Kräußling, A.: A novel approach to the mobile robot localization problem using tracking methods. Submitted to the 13th IASTED International Conference on Robotics and Applications (RA 2007)

    Google Scholar 

  27. Reid, D. B.: An algorithm for tracking multiple targets. IEEE Transaction on Automatic Control 24 (1979) 843–854

    Article  Google Scholar 

  28. Fortmann, T. E., Bar-Shalom, Y., Scheffe M.: Sonar tracking of multiple targets using joint probabilistic data association. IEEE Journal of Oceanic Engineering OE-8(3) (1983)

    Google Scholar 

  29. Kräußling, A.: Tracking multiple objects using the Viterbi algorithm. 3rd International Conference on Informatics in Control, Automation and Robotics, Setubal, Portugal, (ICINCO 2006), also to be published in the Springer book of best papers of ICINCO 2006

    Google Scholar 

  30. Schumitch, B., Thrun, S., Bradski, B., Olukotun, K.: The information – form data association filter. 2005 Conference on Neural Information Processing Systems (NIPS) MIT Press (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Communication, Information Processing and Ergonomics, Research Establishment of Applied Sciences, Bad Neuenahrer Straße 20, D-53343, Wachtberg, Germany

    Andreas Kräußling

Authors
  1. Andreas Kräußling
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Harrow School of Computer Science, The University of Westminster, Watford Road Northwick Park, London, HA1 3TP, UK

    Panagiotis Chountas

  2. School of Informatics, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Ilias Petrounias

  3. Systems Research Institute, Polish Academy of Sciences, Ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Kräußling, A. (2008). Tracking Extended Moving Objects with a Mobile Robot. In: Chountas, P., Petrounias, I., Kacprzyk, J. (eds) Intelligent Techniques and Tools for Novel System Architectures. Studies in Computational Intelligence, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77623-9_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77623-9_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77621-5

  • Online ISBN: 978-3-540-77623-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation