Advanced Optical Terrain Absolute Navigation for Pinpoint Lunar Landing

  • Marco Mammarella
  • Marcos Avilés Rodrigálvarez
  • Andrea Pizzichini
  • Ana María Sánchez Montero


Pin-point landing can only be achieved developing precise Absolute Navigation systems. Craters, for their intrinsic properties, are one of the most suitable and robust features identifiable in lunar landscape. The Optical Terrain Absolute Navigation (OTAN) system provides absolute navigation features and is composed by two main parts: the off-line part, focused on the extraction of the Landmark Database; the on-line part instead is focused on the Real Time identification of the craters and the Orbit Determination process. The presented vision-based approach uses Real-Time crater identification in order to extract relevant features from on-board captured images of the lunar surface. The detected craters are fitted with ellipses and matched to a Lunar Crater Database previously created. The matching of the two sets permits the computation of the absolute position of the camera. A Kalman Filter uses this information and the IMU measurements in order to provide precise complete state space information of the vehicle. In this paper, a detailed description of the complete structure of the Optical Terrain Absolute Navigation system based on craters detection and recognition is provided.


Inertial Measurement Unit Star Tracker Border Detection Lidar Sensor Navigation Filter 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cheng, Y., Ansar, A.: A Landmark Based Position Estimation for Pinpoint Landing on Mars. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA), Barcelona, Spain, pp. 4470–4475 (2005)Google Scholar
  2. 2.
    Trawny, N., Mourikis, A.I., Roumeliotis, S.I.: Coupled Vision and Inertial Navigation for Pin-point Landing. In: NASA Science Technology Conference (2007)Google Scholar
  3. 3.
    Trawny, N., Mourikis, A.I., Roumeliotis, S.I., Johnson, A.E., Montgomery, J.: Vision-Aided Inertial Navigation for Pin-Point Landing using Observations for Mapped Landmarks. Journal of Fields Robotics (2006)Google Scholar
  4. 4.
    Hamel, J.F., Neveu, D., Jean, L.: Feature Matching Navigation Techniques for Lidar-Based Planetary Exploration. In: AIAA Guidance, Navigation and Control Conference and Exhibit (2006)Google Scholar
  5. 5.
    Pham, B.V., Lacroix, S., Devy, M., Drieux, M., Voirin, T.: Landmarks Constellation Matching for Planetary Lander Absolute Localization. In: International Conference on Computer Vision Theory and Applications (VISAPP 2010), Anger, France, May 17-21 (2010)Google Scholar
  6. 6.
    Melloni, S., Mammarella, M., Gil-Fernández, J., Colmenarejo, P.: GNC solution for Lunar Pinpoint and Soft Landing. In: Global Lunar Conference, 11th ILEWG Conference on Exploration and Utilisation of the Moon, Beijing, China, May 31 - June 3 (2010)Google Scholar
  7. 7.
    Lunar Orbital Deta Explorer,
  8. 8.
    PANGU. Planet and Asteroid Natural scene Generation Utility, University of Dundee, UK,
  9. 9.
    Pizzichini, A., Mammarella, M., Colmenarejo-Matellano, P., Melloni, S., Graziano, M., Curti, F.: Inertial Vision Based Navigation Technique For Low Lunar Orbit Position Determination. In: 4th International Conference on Astrodynamics Tools and Techniques (ICATT), Madrid, Spain, May 3-6 (2010)Google Scholar
  10. 10.
    Pizzichini, A., Mammarella, M., Colmenarejo-Matellano, P., Graziano, M., Curti, F.: Known Landmark Navigation for Precise Position Estimation in Lunar Landing Mission. In: Global Lunar Conference, 11th ILEWG Conference on Exploration and Utilisation of the Moon, Beijing, China, May 31 - June 3 (2010)Google Scholar
  11. 11.
    Cheng, Y., Johnson, A.E., Matthies, L.H., Olson, C.F.: Optical Landmark Detection for Spacecraft Navigation. In: 13th Annual AAS/AIAA Space Flight Mechanics Meeting (2003)Google Scholar
  12. 12.
    Parker, J.R.: Algorithms for Image Processing and Computer Vision, pp. 23–29. John Wiley & Sons, Inc., New York (1997)Google Scholar
  13. 13.
    Fitzgibbon, A.W., Pilu, M., Fisher, R.B.: Direct Least Squares Fitting of Ellipses. In: International Conference on Pattern Recognition, Vienna (August 1996)Google Scholar
  14. 14.
    Mammarella, M., Campa, G., Napolitano, M.R., Fravolini, M.L.: Comparison of Point Matching Algorithms for the UAV Aerial Refueling Problem. Journal of Machine Vision and Applications (in press)Google Scholar
  15. 15.
    Lu, C.P., Hager, G.D., Mjolsness, E.: Fast and Globally Con-vergent Pose Estimation from Video Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(6), 610–622 (2000)CrossRefGoogle Scholar
  16. 16.
    Brison, A.E., Ho, Y.C.: Applied Optimal Control, ch. 2. Hemisphere Publishing Corp., Washington DC (1975)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marco Mammarella
    • 1
  • Marcos Avilés Rodrigálvarez
    • 1
  • Andrea Pizzichini
    • 1
  • Ana María Sánchez Montero
    • 1
  1. 1.GMVTres CantosSpain

Personalised recommendations