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Navigation for Satellite Formation Flying

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper deals with the case of a target satellite in an unknown orientation and location with respect to the master satellite. Feature based monocular pose estimation vision system was presented. The results of analysis, implementation and testing of simulation intended for vision-based navigation applications such as rendezvous of satellites and formation flying are shown. The mobile robot was used as the platform for the vision system. Pose estimation algorithms were implemented in Matlab environment. It was obtained that the proposed method is robust on varying and low light conditions.
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Twórcy
  • Warsaw University of Technology, Faculty of Power and Aeronautical Engineering 24 Nowowiejska Str., 00-665 Warsaw, Poland
autor
  • Warsaw University of Technology, Faculty of Power and Aeronautical Engineering 24 Nowowiejska Str., 00-665 Warsaw, Poland
Bibliografia
  • [1] Jacewicz Mariusz, Robert Głębocki. 2016. Navigation for satellites. In Challenges in Automation, Robotics and Measurement Techniques, Advances in Intelligent Systems and Computing, 647-658. Springer.
  • [2] Amzajerdian Farzin, Vincent Roback, Alexander Bulyshev, Paul Brewster. 2015. Imaging flash LIDAR for safe landing on solar system bodies and spacecraft rendezvous and docking. In Proceedings of the SPIE Laser Radar Technology and Applications XX; and Atmospheric Propagation XII. Society of Photographic Instrumentation Engineers.
  • [3] Woods O. John, John A. Christian. 2016. “LIDAR - based relative navigation with respect to non-cooperative objects”. Acta Astronautica 126 : 298-311.
  • [4] Chien Chiun-Hong, Kenneth Baker. 2004. Pose estimation for servicing of orbital replacement units in a cluttered environment. In Proceedings of the IEEE International Conference on Robotics and Automation, 5141-5146. Institute of Electrical and Electronics Engineers.
  • [5] Sharma Sumant, Simone D’Amico. 2016. “Comparative assessment of techniques for initial pose estimation using monocular”. Acta. Astronautica 123 : 435-445.
  • [6] Mikolajczyk Krystian. 2004. “Scale & Affine Invariant Interest Point Detectors”. International Journal of Computer Vision 60 (1) : 63-86.
  • [7] English Chad, Galina Okouneva, Pierre Saint-Cyr, Aradhana Choudhuri, Timothy Johnson Luu. 2011. “Real-time dynamic pose estimation systems in space lessons learned for system design and performance evaluation”. International Journal of Intelligent Control and Systems.
  • [8] Głębocki Robert, Paweł Kicman, Antoni Kopyt. 2015. “Navigation module for mobile robot”. In Progress in Automation, Robotics and Measuring Techniques, 79-85. Springer.
  • [9] Opromolla Roberto, Giancarmine Fasano, Giancarlo Rufino, Michele Grassi. 2015. “Uncooperative pose estimation with a LIDAR-based system”. Acta Astronautica 110 : 287-297.
  • [10] Cropp Alexander, Philip Mclauchlan, Craig Underwood. 2000. “Estimating pose of known target satellite”. Electronics Letters 36 (15) : 1331-1332.
  • [11] Mcclamroch Harris, Chi-Chang Ho. 1992. Autonomous Spacecraft Docking using a Computer Vision System. In Proceedings of the 31st Conference on Decision and Control, 645-650. Institute of Electrical and Electronics Engineers.
  • [12] Petit Audrey, Noela Despre, Francois Chaumette, Scott Provost. 2011. 3D Model-Based Tracking For Space Autonomous Randezvouz. In Proceedings of the 8th Int. ESA Conference on Guidance and Navigation Control Systems. European Space Agency.
  • [13] Palmerini Giovanni, Marco Sabatini, Paolo Gasbarri. 2013. Analysis and tests of visual based techniques for orbital rendezvous operations. In Proceedings of the IEEE Aerospace Conference, 1-15. Institute of Electrical and Electronics Engineers.
  • [14] Gasbarri Paolo, Marco Sabatini, Giovanni Palmerini. 2014. “Ground tests for vision based determination and control of formation flying spacecraft trajectories”. Acta Astronautica 102 : 378-391.
  • [15] Ruel Stephane, Timothy Luu. 2008. Target localization from 3D data for on-orbit autonomous rendezvous and docking. In Proceedings of the IEEE Aerospace Conference, 1-11. Institute of Electrical and Electronics Engineers.
  • [16] Fischler Martin. 1988. “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography”. Comm. of ACM 24 (6) : 381-395.
  • [17] Quan Long, Zhongdan Lan. 1998. Linear N4-point pose determination. In Proceedings of the 6th International Conference on Computer Vision, 778-783. Institute of Electrical and Electronics Engineers.
  • [18] http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/ (2018).
  • [19] Petersen Thomas. 2008. A Comparison of 2D-3D Pose Estimation Methods” Ballerup: Aalborg University.
  • [20] Grunert Johann August. 1842. “Das pothenotische Problem in erweiterter Gestalt nebst über seine Anwendungen in Geodäsie”. Grunerts Archiv für Mathematik und Physik 1 : 238-248.
  • [21] Krenn Rainer. 2008. Simulation of the Docking Phase for the SMART-OLEV Satellite Servicing Mission. In Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS).
  • [22] Fischler Martin. 1988. “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography”. Comm. of ACM 24 (6) : 381-395.
  • [23] Jasiobedzki Piotr, Michael Greenspan, Gerhard Roth. 2001. Pose Determination and Tracking for Autonomous Satellite Capture. In Proceeding of the 6th International Symposium on Artificial Intelligence and Robotics & Automation in Space, 1-8. National Research Council of Canada.
  • [24] Jörgensen John, Jon Harr. 2006. PRISMA – An Autonomous Formation Flying Mission. In ESA Small Satellite Systems and Services Symposium, 1-12. European Space Agency.
Uwagi
1. The following research was done within the project (agreement No. PBS2/B3/17/2013), sponsored by the Polish National Centre for Research and Development.
2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-90334755-be0a-4b43-8610-cb838fea9572
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