So You Think You Can Dance? Rhythmic Flight Performances with Quadrocopters

  • Angela P. Schoellig
  • Hallie Siegel
  • Federico Augugliaro
  • Raffaello D’Andrea

Abstract

This chapter reviews an approach for generating rhythmic flight motions that are executed by quadrocopters and timed to music. It represents a research and artistic experiment, which explores for the first time the potential of using flying vehicles in rhythmic, musical performances. We introduce periodic movements as the basic motion elements of such a performance, and derive control algorithms for guiding the vehicles along the desired motion paths and synchronizing their motion to the music. The vehicle dynamics and constraints are taken into account to determine, prior to flight, which motions are feasible. We demonstrate the resulting multivehicle flight performances at the ETH Zurich Flying Machine Arena.

Keywords

Flying robots  Quadrocopters Rhythmic flight Trajectory planning  Motion feasibility Motion–music synchronization 

References

  1. 1.
    Schoellig AP, Augugliaro F, D’Andrea R (2010) Synchronizing the motion of a quadrocopter to music. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), 2010, pp 3355–3360Google Scholar
  2. 2.
    Schoellig AP, Augugliaro F, D’Andrea R (2010) A platform for dance performances with multiple quadrocopters. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) - workshop on robots and musical expressions, 2010, pp 1–8Google Scholar
  3. 3.
    Schoellig AP, Hehn M, Lupashin S, D’Andrea R (2011) Feasibility of motion primitives for choreographed quadrocopter flight. In: Proceedings of the American control conference (ACC), 2011, pp 3843–3849Google Scholar
  4. 4.
    Schoellig AP, Wiltsche C, D’Andrea R (2012) Feed-forward parameter identification for precise periodic quadrocopter motions. In: Proceedings of the American control conference (ACC), 2012, pp 4313–4318Google Scholar
  5. 5.
    Augugliaro F, Schoellig AP, D’Andrea R (2013) Dance of the flying machines. IEEE Robotics and Automation MagazineGoogle Scholar
  6. 6.
    Varela FJ, Thompson ET, Rosch E (1991) Dance of the flying machines: Methods for Designing and Executing an Aerial Dance Choreography. The embodied mind: cognitive science and human experience. The MIT Press, CambridgeGoogle Scholar
  7. 7.
    Brooks RA (2000) Cambrian intelligence: the early history of the new AI. MIT Press, CambridgeGoogle Scholar
  8. 8.
    Pfeifer R, Bongard J (2007) How the body shapes the way we think: a new view of intelligence. MIT press, CambridgeGoogle Scholar
  9. 9.
    Block B, Kissell JL (2001) The dance: essence of embodiment. Theoretical medicine and bioethics 22(1):5–15CrossRefGoogle Scholar
  10. 10.
    Gray JA (1989) Dance technology: current applications and future trends. ERICGoogle Scholar
  11. 11.
    Gray JA (1984) Dance in computer technology: a survey of applications and capabilities. Interchange 15(4):15–25Google Scholar
  12. 12.
    Kim G, Wang Y, Seo H (2007) Motion control of a dancing character with music. In: Proceedings of the 6th IEEE/ACIS international conference on computer and information science (ICIS), 2007, pp 930–936Google Scholar
  13. 13.
    Kim T-H, Park SI, Shin SY (2003) Rhythmic-motion synthesis based on motion-beat analysis. ACM Trans. Graph. (TOG) 22(3):392–401Google Scholar
  14. 14.
    Bary J, Leaping into dance technology. Connect: information technology at NYU, 2002. http://www.nyu.edu/its/pubs/connect/archives/fall02/bary_dance.pdf
  15. 15.
    Macel E (2007) iDance. Dance MagazineGoogle Scholar
  16. 16.
    Latulipe C, Wilson D, Huskey S, Word M, Carroll A, Carroll E, Gonzalez B, Singh V, Wirth M, Lottridge D (2010) Exploring the design space in technology-augmented dance. In: Extended abstracts on human factors in computing systems. ACM, New York, pp 2995–3000Google Scholar
  17. 17.
    Meador WS, Rogers TJ, O’Neal K, Kurt E, Cunningham C (2004) Mixing dance realities: collaborative development of live-motion capture in a performing arts environment. Computers in Entertainment (CIE) 2(2):12–12CrossRefGoogle Scholar
  18. 18.
    Birringer JH (2002) Dance and media technologies. PAJ J Perform Art 24(1):84–93Google Scholar
  19. 19.
    Lynch A, Majeed B, O’Flynn B, Barton J, Murphy F, Delaney K, O’Mathuna S (2005) A wireless inertial measurement system (WIMS) for an interactive dance environment. J Phys Conf Series 15(1):95CrossRefGoogle Scholar
  20. 20.
    Calvert T, Wilke W, Ryman R, Fox I (2005) Applications of computers to dance. IEEE Comput Graph Appl 25(2):6–12CrossRefGoogle Scholar
  21. 21.
    Chan JC, Leung H, Tang JK, Komura T (2011) A virtual reality dance training system using motion capture technology. IEEE Trans Learn Technol 4(2):187–195CrossRefGoogle Scholar
  22. 22.
    Parrish M (2007) Technology in dance education. In: International handbook of research in arts education. Springer, Dordrecht, pp 1381–1397Google Scholar
  23. 23.
    Smith-Autard J (2003) The essential relationship between pedagogy and technology in enhancing the teaching of dance form. Res Dance Educ 4(2):151–169CrossRefGoogle Scholar
  24. 24.
    Obermaier K, Ars Electronica Futurelab Apparition. http://www.exile.at/apparition/project.html
  25. 25.
    Nakazawa A, Nakaoka S, Ikeuchi K, Yokoi K (2002) Imitating human dance motions through motion structure analysis. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), vol 3, 2002, pp 2539–2544Google Scholar
  26. 26.
    Sousa P, Oliveira JL, Reis LP, Gouyon F (2011) Humanized robot dancing: humanoid motion retargeting based in a metrical representation of human dance styles. Prog Artif Intell 7026:392–406Google Scholar
  27. 27.
    Shinozaki K, Iwatani A, Nakatsu R (2008) Construction and evaluation of a robot dance system. In: Proceedings of the IEEE international symposium on robot and human interactive communication (ROMAN), 2008, pp 366–370Google Scholar
  28. 28.
    Aucouturier J, Ogai Y, Ikegami T (2008) Making a robot dance to music using chaotic itinerancy in a network of fitzhugh-nagumo neurons. Neural information processing, pp 647–656, 2008. http://link.springer.com/chapter/10.1007/978-3-540-69162-4_67
  29. 29.
    Nakaoka S, Kajita S, Yokoi K (2010) Intuitive and flexible user interface for creating whole body motions of biped humanoid robots. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, 2010, pp 1675–1682Google Scholar
  30. 30.
    Tholley IS, Meng QG, Chung PW (2012) Robot dancing: what makes a dance? Adv Mater Res 403:4901–4909Google Scholar
  31. 31.
    Avrunin E, Hart J, Douglas A, Scassellati B (2011) Effects related to synchrony and repertoire in perceptions of robot dance. In: Proceedings of the 6th international conference on Human-robot, interaction, 2011, pp 93–100Google Scholar
  32. 32.
    Grunberg DK, Batula AM, Schmidt EM, Kim YE (2012) Affective gesturing with music mood recognition. In: Proceedings of the 12th IEEE-RAS international conference on humanoid robots, 2012, pp 343–348Google Scholar
  33. 33.
    Ekman P (1992) Are there basic emotions? Psychol Rev 99:550–553Google Scholar
  34. 34.
    Xia G, Dannenberg R, Tay J, Veloso M (2012) Autonomous robot dancing driven by beats and emotions of music. In: Proceedings of the 11th international conference on autonomous agents and multiagent systems-volume 1. International foundation for autonomous agents and multiagent systems, 2012, pp 205–212Google Scholar
  35. 35.
    Meng Q, Tholley I, Chung PW (2012) Robot dancing: adapting robot dance to human preferences. pp. 557–565, 2012Google Scholar
  36. 36.
    Takeda T, Hirata Y, Kosuge K (2007) Dance step estimation method based on hmm for dance partner robot. IEEE Trans Ind Electron 54(2):699–706CrossRefGoogle Scholar
  37. 37.
    Kosuge K, Takeda T, Hirata Y, Endo M, Nomura M, Sakai K, Koizumi M, Oconogi T (2008) Partner ballroom dance robot -PBDR-. SICE J Control Measur Syst Integr 1(1):74–80CrossRefGoogle Scholar
  38. 38.
    Michalowski MP, Simmons R, Kozima H (2009) Rhythmic attention in child-robot dance play. In: Proceedings of the 18th IEEE international symposium on robot and human interactive, communication, 2009, pp 816–821Google Scholar
  39. 39.
    Baillieul J, Ozcimder K (2012) The control theory of motion-based communication: Problems in teaching robots to dance. In: Proceedings of the American control conference (ACC), 2012, pp 4319–4326Google Scholar
  40. 40.
    Murphy R, Shell D, Guerin A, Duncan B, Fine B, Pratt K, Zourntos T (2011) A midsummer night’s dream (with flying robots). Auton Robot 30(2):143–156CrossRefGoogle Scholar
  41. 41.
    Catton P (2011) Culture city online: dances with robots. The Wall Street Journal - Metropolis Blog. http://blogs.wsj.com/metropolis/2011/07/15/culture-city-online-dances-with-robots/
  42. 42.
    Augugliaro F, Schoellig AP, D’Andrea R (2012) Generation of collision-free trajectories for a quadrocopter fleet: a sequential convex programming approach. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), 2012, pp 1917–1922Google Scholar
  43. 43.
    Mellinger D, Kumar V (2011) Minimum snap trajectory generation and control for quadrotors. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), 2011, pp 2520–2525Google Scholar
  44. 44.
    Hughes PC (1986) Spacecraft attitude dynamics. Wiley, New YorkGoogle Scholar
  45. 45.
    Dixon S (2006) BeatRoot: an interactive beat tracking and visualisation system (software tool). http://www.eecs.qmul.ac.uk/simond/beatroot
  46. 46.
    Sofras P (2006) Dance composition basics: capturing the choreographer’s craft. Human Kinetics, ChampaignGoogle Scholar
  47. 47.
    Minton SC (2007) Choreography: a basic approach using improvisation, 3rd edn. Human Kinetics, ChampaignGoogle Scholar
  48. 48.
    Tolstov GP, Silverman RA (1962) Fourier series. Courier Dover Publications, New YorkGoogle Scholar
  49. 49.
    Fraleigh SH (1987) Dance and the lived body: a descriptive aesthetics. University of Pittsburgh Press, PittsburghGoogle Scholar
  50. 50.
    Augugliaro F (2011) Dancing quadrocopters - trajectory generation, feasibility and user interface. Master’s thesis, ETH Zurich, Switzerland, 2011. http://dx.doi.org/10.3929/ethz-a-007328864
  51. 51.
    How J, Behihke B, Frank A, Dale D, Vian J (2008) Real-time indoor autonomous vehicle test environment. IEEE Contr Syst Mag 28(2):51–64CrossRefGoogle Scholar
  52. 52.
    Lupashin S, Schoellig AP, Sherback M, D’Andrea R (2010) A simple learning strategy for high-speed quadrocopter multi-flips. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), 2010, pp 1642–1648Google Scholar
  53. 53.
    Hanna JL (1987) To dance is human: a theory of nonverbal communication. University of Chicago Press, ChicagoGoogle Scholar
  54. 54.
    Augugliaro F, D’Andrea R (2013) Admittance control for physical human-quadrocopter interaction. In: Proceedings of the European control conference (ECC), 2013, pp 1805–1810Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Angela P. Schoellig
    • 1
  • Hallie Siegel
    • 2
  • Federico Augugliaro
    • 2
  • Raffaello D’Andrea
    • 2
  1. 1.Institute for Aerospace StudiesUniversity of TorontoTorontoCanada
  2. 2.Institute for Dynamic Systems and ControlETH ZurichZurichSwitzerland

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