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Camera-Based Tracking for Rendezvous and Proximity Operation of a Satellite

  • Nassir W. OumerEmail author
  • Giorgio Panin
Conference paper

Abstract

This paper focuses on vision-based detection and tracking of a nozzle of a satellite for rendezvous and proximity operation at very close range. For this purpose, on-board cameras can provide an effective solution in accuracy and robustness during the approach. However, the illumination conditions in space are especially challenging, due to the direct sunlight exposure, and to the glossy surface of a satellite. We propose an efficient tracking method that can be realized on standard processor, robustly dealing with the above issues exploiting model and image edges. The algorithm has been validated at the facility of the European Proximity Operations Simulator of DLR, using a ground simulation system that is able to reproduce sunlight conditions through a high power floodlight source, satellite surface properties using reflective foils, as well as complex motion trajectories with ground truth data.

Keywords

Stereo Image Stereo Match Stereo Camera Local Tracking Reprojection Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Xu, W., Liang, B., Gao, D., Xu, Y.: A Universal On-orbit Servicing System Used in the Geostationary Orbit. Advances in Space Research 48, 95–119 (2011)CrossRefGoogle Scholar
  2. 2.
    Miravet, C., Pascual, L., Krouch, E., Delcura, J.M.: An Image-based Sensor System for Autonmous Rendezvous with Uncooperative Satellites. In: 7th International ESA Conference on Guidance, Navigation and Control Systems (June 2008)Google Scholar
  3. 3.
    Samson, C., English, C., Deslauriers, A., Christie, I., Blais, F., Ferrie, F.: Neptec 3D laser camera system : From space mission STS-105 to terresterial applications, Canadian Aeronotics and Space Journal (2004)Google Scholar
  4. 4.
    Dionnet, F., Marchand, E.: Robust Stereo Tracking for Space applications. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, October 29-November 2 (2007)Google Scholar
  5. 5.
    Comport, A.I., Marchand, E., Pressigout, M., Chaumette, F.: Real-Time Markerless Tracking for Augmented Reality: The Virtual Visual Servoing Framework. IEEE Transaction on Visualization and Computer Graphics 12(4), 615–628 (2006)CrossRefGoogle Scholar
  6. 6.
    Petit, A., March, E., Kanani, K.: Vision-based Space Autonomous Rendezvous: A Case Study. In: EEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 619–624 (2011)Google Scholar
  7. 7.
    Drummond, T., Cipolla, R.: Real-Time Visual Tracking of Complex Structures. IEEE Trans on Pattern Analysis and Machine Intelligence, 932–946 (2002)Google Scholar
  8. 8.
    Drummond, T., Cipolla, R.: Visual Tracking and Control using Lie Algebras. IEEE Computer Society Computer Vision and Pattern Recognition 2, 2652–2659 (1999)Google Scholar
  9. 9.
    John Canny, F.: A computational Approach to Edge Detection. IEEE-PAMI 8(6), 679–698 (1986)CrossRefGoogle Scholar
  10. 10.
    Choi, C., Christensen, H.I.: Real-time 3D Model-based Tracking Using Edge and Keypoint Features for Robotic Manipulation. In: IEEE International Conference on Robotics and Automation, May 3-8, pp. 4048–4055 (2010)Google Scholar
  11. 11.
    Ladrón De Guevara, I., Muñoz, J., Cózar, O.D., Blázquez, E.B.: Robust Fitting of Circle Arcs. Journal of Mathematical Imaging and Vision 40(2), 147–161 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
  12. 12.
    Harris, C., Stennet, C.: RAPiD a video-rate object tracker. Proceedings of the British Machine Vision Conference, 73–77 (September 1990)Google Scholar
  13. 13.
    Lowe, D.G.: Fitting parametrized Three-Dimensional Models to Images. IEEE Transaction Pattern Analysis and Machine Intelligence 13(5), 441–450 (1991)CrossRefMathSciNetGoogle Scholar
  14. 14.
    Strobl, K.H., Hirzinger, G.: Optimal Hand-Eye Calibration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 4647–4653 (2006)Google Scholar
  15. 15.
    Oumer, N.W., Panin, G.: 3D point tracking and pose estimation of a space object using stereo images. In: 21st International Conference on Pattern Recognition, Tsukuba, Japan, pp. 796–800 (2012)Google Scholar
  16. 16.
    Oumer, N.W., Panin, G.: Monocular 3D Pose Tracking of a Specular Object. In: 9th International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, January 5-8, vol. 3, pp. 458–465 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Robotics and Mechatornics Center, German Aerospace CenterKölnGermany

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