journal article·2007-12-01Open access

Artificial evolution of the morphology and kinematics in a flapping-wing mini-UAV

E de Margerie, J B Mouret, S Doncieux, J-A Meyer

Bioinspiration & Biomimetics· Volume 2· Issue 4

Abstract

Birds demonstrate that flapping-wing flight (FWF) is a versatile flight mode, compatible with hovering, forward flight and gliding to save energy. This extended flight domain would be especially useful on mini-UAVs. However, design is challenging because aerodynamic efficiency is conditioned by complex movements of the wings, and because many interactions exist between morphological (wing area, aspect ratio) and kinematic parameters (flapping frequency, stroke amplitude, wing unfolding). Here we used artificial evolution to optimize these morpho-kinematic features on a simulated 1 kg UAV, equipped with wings articulated at the shoulder and wrist. Flight tests were conducted in a dedicated steady aerodynamics simulator. Parameters generating horizontal flight for minimal mechanical power were retained. Results showed that flight at medium speed (10-12 m s(-1)) can be obtained for reasonable mechanical power (20 W kg(-1)), while flight at higher speed (16-20 m s(-1)) implied increased power (30-50 W kg(-1)). Flight at low speed (6-8 m s(-1)) necessitated unrealistic power levels (70-500 W kg(-1)), probably because our simulator neglected unsteady aerodynamics. The underlying adaptation of morphology and kinematics to varying flight speed were compared to available biological data on the flight of birds.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Biomimetic flight and propulsion mechanisms · Fish Ecology and Management Studies · Animal Behavior and Reproduction

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (34)

Show source-provided references
1. Angeli A Filliat D Doncieux S Meyer J-A · Proc. Eur. Micro Aerial Vehicles (EMAV 2006) Conf. · 2006
2. Askew G N · J. Exp. Biol. · 2001 · 204 · 360110.1242/jeb.204.21.3601 ↗
3. Barate R · Bioinsp. Biomim. · 2006 · 1 · 7610.1088/1748-3182/1/3/002 ↗
4. 10.1098/rsif.2006.012810.1098/rsif.2006.0128 ↗
5. 10.1162/10636560577466689510.1162/106365605774666895 ↗
6. DeLaurier J · Can. Aeronaut. Space J. · 1999 · 45 · 72
7. 10.1038/3633010.1038/36330 ↗
8. Doncieux S Mouret J Muratet L Meyer J-A · Proc. Journées MicroDrones · 2004
9. Druot T · 2004
10. 10.1098/rstb.1984.005210.1098/rstb.1984.0052 ↗
11. 10.1038/384626a010.1038/384626a0 ↗
12. Goldberg D E · Genetic Algorithms in Search, Optimization, and Machine Learning · 1989
13. Greenewalt C H · Smithson. Misc. Collect. · 1962 · 144 · 1
14. Greenewalt C H · Trans. Am. Phil. Soc. · 1975 · 65 · 110.2307/1006161 ↗
15. Hedrick T L · J. Exp. Biol. · 2002 · 205 · 138910.1242/jeb.205.10.1389 ↗
16. Meyer J-A · Handbook of Robotics · 2007
17. Mouret J-B Doncieux S Druot T Meyer J-A · 2007
18. 10.1016/j.robot.2004.09.01710.1016/j.robot.2004.09.017 ↗
19. Norberg U M · Vertebrate Flight · 199010.1007/978-3-642-83848-4 ↗
20. 10.1002/jmor.1001310.1002/jmor.10013 ↗
21. Park K J · J. Exp. Biol. · 2001 · 204 · 274110.1242/jeb.204.15.2741 ↗
22. Pennycuick C J · J. Exp. Biol. · 1996 · 199 · 161310.1242/jeb.199.7.1613 ↗
23. Rakotomamonjy T Le Moing T Ouladsine M · EMAV 2004 Conf. · 2004
24. Rayner J M V · J. Exp. Biol. · 1999 · 202 · 344910.1242/jeb.202.23.3449 ↗
25. Salles R Schiele A · Proc. 8th ESA Workshop on Advanced Space Technologies for Robotics and Automation ASTRA 2004 · 2004
26. Selig M · Summary of Low Speed Airfoil Data · 1997 · 2
27. Shim S Y Kim S J Kim C H · Proc. 9th Int. Conf. on the Simulation and Synthesis of Living Systems · 2004
28. Smith R · 2006
29. Tobalske B W · J. Exp. Biol. · 1996 · 199 · 26310.1242/jeb.199.2.263 ↗
30. 10.1038/nature0128410.1038/nature01284 ↗
31. van Breugel F Lipson H · GECCO 2005 · 2005
32. Van den Berg C · J. Exp. Biol. · 1995 · 198 · 165510.1242/jeb.198.8.1655 ↗
33. Vogel S · Life in Moving Fluids · 1994
34. Withers P C · J. Exp. Biol. · 1981 · 90 · 14310.1242/jeb.90.1.143 ↗