2026-07-23T06:31:05Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:6189 2024-03-06T10:38:27Z ddc:004 open_access

Love Thy Neighbor: V-Formation as a Problem of Model Predictive Control (Invited Paper) Yang, Junxing Grosu, Radu Smolka, Scott A. Tiwari, Ashish bird flocking v-formation model predictive control particle swarm optimization 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Junxing Yang and Radu Grosu and Scott A. Smolka and Ashish Tiwari 2016 Is Part Of LIPIcs, Volume 59, 27th International Conference on Concurrency Theory (CONCUR 2016) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CONCUR.2016.4 urn:nbn:de:0030-drops-61896 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2016.4 eng https://creativecommons.org/licenses/by/3.0/legalcode