Generating and analyzing hierarchical interaction in a flock of robotic swarms

One of the popular approaches for the self-organized flocking of artificial agents is based on a computer animation model called Boid. This model reproduces flocking motion using three simple behavioral rules: repulsion, attraction, and alignment. However, the flocking performance largely depends on how these rules are configured, and no general guideline exists for the configuration. This paper introduces hierarchical interaction-based flocking by employing individuals that can switch their roles. Robots can move as leaders or followers depending on the situation. The flocking performance is evaluated, and the swarming behavior is analyzed in a scenario where robots travel alternately between two landmarks.