Advertisement

Autonomous Helicopter Tracking and Localization Using a Self-Surveying Camera Array

  • Masayoshi Matsuoka
  • Alan Chen
  • Surya P. N. Singh
  • Adam Coates
  • Andrew Y. Ng
  • Sebastian Thrun
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 25)

Summary

This paper describes an algorithm that tracks and localizes a helicopter using a ground-based trinocular camera array. The three cameras are placed independently in an arbitrary arrangement that allows each camera to view the helicopter’s flight volume. The helicopter then flies an unplanned path that allows the cameras to self-survey utilizing an algorithm based on structure from motion and bundle adjustment. This yields the camera’s extrinsic parameters allowing for real-time positioning of the helicopter’s position in a camera array based coordinate frame. In fielded experiments, there is less than a 2m RMS tracking error and the update rate of 20Hz is comparable to DGPS update rates. This system has successfully been integrated with an IMU to provide a positioning system for autonomous hovering.

Keywords

structure from motion bundle adjustment self-surveying cameras camera tracking camera localization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    P. Maybeck, Stochastic Models, Estimation, and Control, Volume 1. Academic Press, Inc, 1979.Google Scholar
  2. 2.
    E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision. Prentice Hall, 1998.Google Scholar
  3. 3.
    C. Poelman and T. Kanade, “A paraperspective factorization method shape and motion recovery,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 3, Mar. 1997.Google Scholar
  4. 4.
    D. A. Forsyth and J. Ponce, Computer Vision: A Modern Approach. Prentice Hall, 2003.Google Scholar
  5. 5.
    M. Whalley, M. Freed, M. Takahashi, D. Christian, A. Patterson-Hine, G. Schulein, and H. R., “The NASA / Army Autonomous Rotorcraft Project,” in Proceedings of the American Helicopter Society 59th Annual Forum, Phoenix, Arizona, 2003.Google Scholar
  6. 6.
    S. Saripalli, J. Montgomery, and G. Sukhatme, “Visually-guided landing of an autonomous aerial vehicle,” IEEE Transactions on Robotics and Automation, 2002.Google Scholar
  7. 7.
    J. M. Roberts, P. I. Corke, and G. Buskey, “Low-cost flight control system for a small autonomous helicopter,” in IEEE International Conference on Robotics and Automation, 2003.Google Scholar
  8. 8.
    P. Liang, P. Chang, and S. Hackwood, “Adaptive self-calibration of vision-based robot systems,” IEEE Transactions on Systems, Man and Cybernetics, vol. 19, no. 4, pp. 811–824, July 1989.CrossRefGoogle Scholar
  9. 9.
    G. Mayer, H. Utz, and G. Kraetzschmar, “Towards autonomous vision self-calibration for soccer robots,” Proc. of the Intelligent Robot and Systems (IROS) Conference, vol. 1, pp. 214–219, 2002.Google Scholar
  10. 10.
    J. Knight and I. Reid, “Self-calibration of a stereo rig in a planar scene by data combination,” In Proc. of the Internatoinal Conference on Pattern Recognition, pp. 1411–1414, Sept. 2000.Google Scholar
  11. 11.
    Z. Zhang, “Motion and structure of four points from one motion of a stereo rig with unknown extrinisic parameters,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 12, Dec. 1995.Google Scholar
  12. 12.
    S. Blackman, “Multiple hypothesis tracking for multiple target tracking,” IEEE Aerospace and Electronic Systems Magazine, vol. 19, no. 1, Jan. 2004.Google Scholar
  13. 13.
    M. Han and T. Kanade, “Perspective factorization methods for euclidean reconstruction,” Carnegie Mellon, Tech. Rep. CMU-RI-TR-99-22, Aug. 1999.Google Scholar
  14. 14.
    S. Thrun, G. Bradski, and D. Russakoff, “Struction from motion,” Feb. 2004, lecture Notes from CS223b.Google Scholar
  15. 15.
    A. Ng, A. Coates, M. Diel, V. Ganapathi, J. Schulte, B. Tse, E. Berger, and E. Liang, “Inverted autonomous helicopter flight via reinforcement learning,” International Symposium on Experimental Robotics, 2004.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Masayoshi Matsuoka
    • 1
  • Alan Chen
    • 1
  • Surya P. N. Singh
    • 1
  • Adam Coates
    • 1
  • Andrew Y. Ng
    • 1
  • Sebastian Thrun
    • 1
  1. 1.Stanford UniversityStanford

Personalised recommendations