Love Thy Neighbor: V-Formation as a Problem of Model Predictive Control (Invited Paper)

Authors Junxing Yang, Radu Grosu, Scott A. Smolka, Ashish Tiwari

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Junxing Yang
Radu Grosu
Scott A. Smolka
Ashish Tiwari

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Junxing Yang, Radu Grosu, Scott A. Smolka, and Ashish Tiwari. Love Thy Neighbor: V-Formation as a Problem of Model Predictive Control (Invited Paper). In 27th International Conference on Concurrency Theory (CONCUR 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 59, pp. 4:1-4:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


We present a new formulation of the V-formation problem for migrating birds in terms of model predictive control (MPC). In our approach, to drive a collection of birds towards a desired formation, an optimal velocity adjustment (acceleration) is performed at each time-step on each bird's current velocity using a model-based prediction window of $T$ time-steps. We present both centralized and distributed versions of this approach. The optimization criteria we consider are based on fitness metrics of candidate accelerations that birds in a V-formations are known to benefit from, including velocity matching, clear view, and upwash benefit. We validate our MPC-based approach by showing that for a significant majority of simulation runs, the flock succeeds in forming the desired formation. Our results help to better understand the emergent behavior of formation flight, and provide a control strategy for flocks of autonomous aerial vehicles.
  • bird flocking
  • v-formation
  • model predictive control
  • particle swarm optimization


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  1. Eduardo F Camacho and Carlos Bordons Alba. Model Predictive Control. Springer Science &Business Media, 2013. Google Scholar
  2. C Cutts and J Speakman. Energy savings in formation flight of pink-footed geese. The Journal of Experimental Biology, 189(1):251-261, 1994. Google Scholar
  3. G Dimock and M Selig. The aerodynamic benefits of self-organization in bird flocks. Urbana, 51:61801, 2003. Google Scholar
  4. Gary William Flake. The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation. MIT Press, 1998. Google Scholar
  5. WJ Hamilton. Social aspects of bird orientation mechanisms. Animal Orientation and Navigation,, pages 57-71, 1967. Google Scholar
  6. Frank H Heppner, Jeffrey L Convissar, Dennis E Moonan Jr, and John GT Anderson. Visual angle and formation flight in Canada geese (Branta Canadensis). The Auk,, pages 195-198, 1985. Google Scholar
  7. Dietrich Hummel. Aerodynamic aspects of formation flight in birds. Journal of Theoretical Biology, 104(3):321-347, 1983. Google Scholar
  8. Andre Nathan and Valmir C Barbosa. V-like formations in flocks of artificial birds. Artificial Life, 14(2):179-188, 2008. Google Scholar
  9. Craig W Reynolds. Flocks, herds and schools: A distributed behavioral model. In ACM Siggraph Computer Graphics, volume 21, pages 25-34. ACM, 1987. Google Scholar
  10. Forrest Stonedahl and Uri Wilensky. Finding forms of flocking: Evolutionary search in ABM parameter-spaces. In Multi-Agent-Based Simulation XI, pages 61-75. Springer, 2011. Google Scholar
  11. Henri Weimerskirch, Julien Martin, Yannick Clerquin, Peggy Alexandre, and Sarka Jiraskova. Energy saving in flight formation. Nature, 413(6857):697-698, 2001. Google Scholar