Experiments in Fluids

, Volume 49, Issue 3, pp 557–569 | Cite as

Extracting micro air vehicles aerodynamic forces and coefficients in free flight using visual motion tracking techniques

Research Article


This paper describes a methodology to extract aerial vehicles’ aerodynamic characteristics from visually tracked trajectory data. The technique is being developed to study the aerodynamics of centimeter-scale aircraft and develop flight simulation models. Centimeter-scale aircraft remains a largely unstudied domain of aerodynamics, for which traditional techniques like wind tunnels and computational fluid dynamics have not yet been fully adapted and validated. The methodology takes advantage of recent progress in commercial, vision-based, motion-tracking systems. This system dispenses from on-board navigation sensors and enables indoor flight testing under controlled atmospheric conditions. Given the configuration of retro-reflective markers affixed onto the aerial vehicle, the vehicle’s six degrees-of-freedom motion can be determined in real time. Under disturbance-free conditions, the aerodynamic forces and moments can be determined from the vehicle’s inertial acceleration, and furthermore, for a fixed-wing vehicle, the aerodynamic angles can be plotted from the vehicle’s kinematics. By combining this information, we can determine the temporal evolution of the aerodynamic coefficients, as they change throughout a trajectory. An attractive feature of this technique is that trajectories are not limited to equilibrium conditions but can include non-equilibrium, maneuvering flight. Whereas in traditional wind-tunnel experiments, the operating conditions are set by the experimenter, here, the aerodynamic conditions are driven by the vehicle’s own dynamics. As a result, this methodology could be useful for characterizing the unsteady aerodynamics effects and their coupling with the aircraft flight dynamics, providing insight into aerodynamic phenomena taking place at centimeter scale flight.


  1. Albertani R, Stanford B, Hubner J, Ifju P (2007) Aerodynamic coefficients and deformation measurements on flexible micro air vehicle wings. Exp Mech 47:625–635CrossRefGoogle Scholar
  2. Bevington P (2002) Data reduction and error analysis for the physical sciences, 3rd edn. McGraw-Hill ScienceGoogle Scholar
  3. Brockwell P, Davis R (2006) Time series: theory and methods, 2nd edn. Springer, New YorkGoogle Scholar
  4. Burk SCW Jr (1975) Radio-controlled model design and testing techniques for stall/spin evaluation of general-aviation aircraft. National Business Aircraft MeetingGoogle Scholar
  5. Dickinson M, Gotz K (1996) The wake dynamics and flight forces of the fruit fly Drosophila melanogasterGoogle Scholar
  6. el Hak MG (2001) Micro-air-vehicles: can they be controlled better? J Aircr 38(3):419–429CrossRefGoogle Scholar
  7. John D, Anderson J (2001) Fundamentals of aerodynamics, 3rd edn. McGraw-HillGoogle Scholar
  8. Marey E (1890) Le vol des oiseaux. G. Masson, ParisGoogle Scholar
  9. Merzkirch W (1987) Flow visualization. Academic Press, Inc., OrlandoMATHGoogle Scholar
  10. Mueller T (1985) The influence of laminar separation and transition on low Reynolds number airfoil hysteresis. J Airc (ISSN 0021-8669) 22:763–770Google Scholar
  11. Mueller TJ (ed) (2001) Fixed and flapping wing aerodynamics for micro air vehicle applications. Progress in Astronautics and Aeronautics. American Institute of Aeronautics and AstronauticsGoogle Scholar
  12. Nicoud JD, Zufferey JC (2002) Toward indoor flying robots. IEEE International Robotics Systems ConferenceGoogle Scholar
  13. Pelletier A, Mueller TJ (2000) Low reynolds number aerodynamics of low-aspect-ratio, thin/flat/ cambered-plate wings. AIAA J Aircr 37(5):825–832Google Scholar
  14. Pines DJ, Bohorquez F (2002) Challenges facing future micro-air-vehicle development. J Aircr 43(2)Google Scholar
  15. Plantraco microflight (2008). http://www.plantraco.com/
  16. Rayner J, Aldridge H (1985) Three-dimensional reconstruction of animal flight paths and the turning flight of microchiropteran bats. J Exp Biol 118(1):247–265Google Scholar
  17. Rhinehart M, Mettler B (2008) Extracting aerodynamic coefficients using direct trajectory sampling. AIAA-2008-6899. AIAA Conference on Guidance Navigation and ControlGoogle Scholar
  18. Stengel RF (2004) Flight dynamics. Princeton University Press, PrincetonGoogle Scholar
  19. Stevens B, Lewis F (1992) Aircraft control and simulation. WileyGoogle Scholar
  20. Suit WT (1972) Aerodynamic parameters of the navion airplane extracted from flight data. NASA Technical Note TN D-6643, NASAGoogle Scholar
  21. Sunada S, Kawachi K (2002) Comparison of wing characteristics at an ultralow reynolds number. J Aircr 39(2):331–338CrossRefGoogle Scholar
  22. Tani I (1964) Low-speed flows involving bubble separations. Prog Aerosp Sci 5:70–103CrossRefGoogle Scholar
  23. Vicon: Vicon mx hardware system reference (2006) http://www.vicon.com/index.html
  24. Wood R, Avadhanula S, Steltz E, Seeman M, Entwistle J, Bachrach A, Barrows G, Sanders S, Fearing R (2007) An autonomous palm-sized gliding micro air vehicle. IEEE Robot Autom Mag 14(2):82–91CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Department of Aerospace Engineering and MechanicsUniversity of MinnesotaMinneapolisUSA

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