Love Thy Neighbor: V-Formation as a Problem of Model Predictive Control (Invited Paper)
Junxing Yang, Radu Grosu, Scott A. Smolka, Ashish Tiwari · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 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.