License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CONCUR.2016.4
URN: urn:nbn:de:0030-drops-61896
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2016/6189/
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Yang, Junxing ; Grosu, Radu ; Smolka, Scott A. ; Tiwari, Ashish

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

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Abstract

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.

BibTeX - Entry

@InProceedings{yang_et_al:LIPIcs:2016:6189,
  author =	{Junxing Yang and Radu Grosu and Scott A. Smolka and Ashish Tiwari},
  title =	{{Love Thy Neighbor: V-Formation as a Problem of Model Predictive Control (Invited Paper)}},
  booktitle =	{27th International Conference on Concurrency Theory (CONCUR 2016)},
  pages =	{4:1--4:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-017-0},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{59},
  editor =	{Jos{\'e}e Desharnais and Radha Jagadeesan},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2016/6189},
  URN =		{urn:nbn:de:0030-drops-61896},
  doi =		{10.4230/LIPIcs.CONCUR.2016.4},
  annote =	{Keywords: bird flocking, v-formation, model predictive control, particle swarm optimization}
}

Keywords: bird flocking, v-formation, model predictive control, particle swarm optimization
Collection: 27th International Conference on Concurrency Theory (CONCUR 2016)
Issue Date: 2016
Date of publication: 24.08.2016

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