  We present a novel approach to the formation controlling of aerial robot
swarms that demonstrates the flocking behavior. The proposed method stems from
the Unmanned Aerial Vehicle (UAV) dynamics; thus, it prevents any unattainable
control inputs from being produced and subsequently leads to feasible
trajectories. By modeling the inter-agent relationships using a pairwise energy
function, we show that interacting robot swarms constitute a Markov Random
Field. Our algorithm builds on the Mean-Field Approximation and incorporates
the collective behavioral rules: cohesion, separation, and velocity alignment.
We follow a distributed control scheme and show that our method can control a
swarm of UAVs to a formation and velocity consensus with real-time collision
avoidance. We validate the proposed method with physical and high-fidelity
simulation experiments.
