Skip to main content
Springer Nature Link
Log in

An Improved Evolvable Oscillator and Basis Function Set for Control of an Insect-Scale Flapping-Wing Micro Air Vehicle

  • Regular Paper
  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

This paper introduces an improved evolvable and adaptive hardware oscillator design capable of supporting adaptation intended to restore control precision in damaged or imperfectly manufactured insect-scale flapping-wing micro air vehicles. It will also present preliminary experimental results demonstrating that previously used basis function sets may have been too large and that significantly improved learning times may be achieved by judiciously culling the oscillator search space. The paper will conclude with a discussion of the application of this adaptive, evolvable oscillator to full vehicle control as well as the consideration of longer term goals and requirements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Gallagher J, Oppenheimer M. An improved evolvable oscillator for all flight mode control of an insect-scale flapping wing micro air vehicle. In Proc. the 2011 IEEE Congress on Evolutionary Computation, June 2011, pp.417–425.

  2. Gallagher J, Doman D, Oppenheimer M. The technology of the gaps: An evolvable hardware synthesized oscillator for the control of a flapping-wing micro air vehicle. IEEE Transactions on Evolutionary Computation, in press.

  3. Gallagher J, Oppenheimer M. Cross-layer learning in an evolvable oscillator for in-flight controller adaptation in a flapping-wing micro air vehicle. In Proc. the 45th Asillomar Conference on Signals, Systems, and Computers, Nov. 2011, pp.1547–1551.

  4. Greenwood G, Tyrrell A. Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems. Wiley-IEEE Press, 2006.

  5. Goldberg D. Genetic Algorithms in Search, Optimization, and Machine Learning. Boston, MA, USA: Addison-Wesley, 1989.

    MATH  Google Scholar 

  6. Fogel D. System Identification through Simulated Evolution: A Machine Learning Approach to Modeling. Ginn Press, 1991.

  7. Bäck T, Hammel U, Schwefel H. Evolutionary computation: Comments on the history and current state. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 3–17.

    Article  Google Scholar 

  8. Wood R. The first takeoff of a biologically-inspired at-scale robotic insect. IEEE Transactions on Robotics, 2008, 24(2): 341–347.

    Article  Google Scholar 

  9. Doman D, Oppenheimer M, Sigthorsson D. Dynamics and control of a minimally actuated biomimetic vehicle: Part i — Aerodynamic model. In Proc. the AIAA Guidance, Navigation, and Control Conference, August 2009.

  10. Doman D, Oppenheimer M, Sigthorsson D. Dynamics and control of a minimally actuated biomimetic vehicle: Part ii — Control. In Proc. the AIAA Guidance, Navigation, and Control Conference, August 2009.

  11. Gallagher J, Doman D, Oppenheimer M. Practical in-flight altitude controller learning in a flapping-wing micro air vehicle. Technical Report 12-01, Department of Computer Science and Engineering, Wright State University, 2012.

  12. Doman D, Oppenheimer M, Bolender M, Sigthorsson D. Altitude control of a single degree of freedom flapping wing micro air vehicle. In Proc. the AIAA Guidance, Navigation, and Control Conference, August 2009.

  13. Kramer G, Gallagher J. Ananalysis of the search performance of a mini-population evolutionary algorithm for a robot locomotion control problem. In Proc. the 2005 IEEE Congress on Evolutionary Computation, Sept. 2005, pp.2768–2775.

  14. Vigraham S, Gallagher J. A space saving digital VLSI evolutionary engine for CTRNN-EH devices. In Proc. the 2005 CEC, Sept. 2005, pp.2483–2490.

  15. Kruskal W, Wallis A. Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 1952, 47(260): 583–621.

    Article  MATH  Google Scholar 

  16. Mann H, Whitney D. On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 1947, 18(1): 50–60.

    Article  MathSciNet  MATH  Google Scholar 

  17. Schenato L, Wu W, Sastry S. Attitude control for a micromechanical flying insect via sensor output feedback. IEEE Transactions on Robotics and Automation, 2004, 20(1): 93–106.

    Article  Google Scholar 

  18. Deng X, Schenato L, Sastry S. Flapping flight for biomimetic robotic insects: Part ii — Flight control design. IEEE Transactions of Robotics, 2006, 22(4): 789–803.

    Article  Google Scholar 

  19. Epstein M, Waydo S, Fuller S, Dickson W, Straw A, Dickinson M, Murray R. Biologically inspired feedback design for drosophila flight. In Proc. the 26th American Control Conference (ACC), July 2007, pp.3395–3401.

  20. Augustsson P, Wolff K, Nordin P. Creation of a learning, flying robot by means of evolution. In Proc. of the 2002 Conference on Genetic and Evolutionary Computation (GECCO2002), July 2002, pp.1279–1285.

  21. van Breugel F, Lipson H. Evolving buildable flapping ornithropters. In Proc. the 2005 Conference on Genetic and Evolutionary Computation, June 2005.

  22. Hunt R, Hornby G, Lohn J. Toward evolved flight. In Proc. the 2005 Conference on Genetic and Evolutionary Computation (GECCO2005), June 2005, pp.957–964.

  23. Mouret J B, Doncieux S, Meyer J A. Incremental evolution of target-following neuro-controllers for flapping-wing animats. In Lecture Notes in Computer Science 4095, Nolfi S, Baldassarre G, Calabretta R, Hallam J, Marocco D, Meyer J A, Miglino O, Meyer J, Parisi D (eds.), Springer Berlin/Heidelberg, 2006, pp.606–618.

  24. Weng L, Cai W, Zhang M, Liao X, Song D. Neural-memory based control of micro air vehicles (MAVS) with flapping wings. In Lecture Notes in Computer Science 4491, Liu D, Fei S, Hou Z G, Zhang H, Sun C (eds.), Springer Berlin/Heidelberg, 2007, pp.70–80.

  25. Guo Q, Hu M, Wei R, Xu J, Song H. Hovering control based on fuzzy neural networks for biomimetic flying robotic. In Proc. the IEEE Int. Conf. Information and Automation 2008 (ICIA2008), June 2008, pp.504–508.

  26. Boddhu S, Gallagher J. Evolved neuromorphic flight control for a flapping-wing mechanical insect. In Proc. the 2008 IEEE Congress on Evolutionary Computation, June 2008, pp.1744–1751.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Wright State University, Dayton, Ohio, 45435-0000, U.S.A.

    John C. Gallagher (Senior Member, IEEE)

  2. Control Sciences Branch, Air Force Research Laboratory, WPAFB, Ohio, 45433-7531, U.S.A.

    Michael W. Oppenheimer (Senior Member, IEEE)

Authors
  1. John C. Gallagher
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Michael W. Oppenheimer
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to John C. Gallagher.

Additional information

This material was assigned a clearance of CLEARED on 16 Dec. 2011 with case number 88ABW-2011-6488.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

(DOC 15.4 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gallagher, J.C., Oppenheimer, M.W. An Improved Evolvable Oscillator and Basis Function Set for Control of an Insect-Scale Flapping-Wing Micro Air Vehicle. J. Comput. Sci. Technol. 27, 966–978 (2012). https://doi.org/10.1007/s11390-012-1277-1

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11390-012-1277-1

Keywords