Animal swarms displaying a variety of typical flocking patterns would not exist without underlying safe, optimal and stable dynamics of the individuals. These patterns can be efficiently reconstructed with simple flocking models, based on three simple rules: cohesion of the flock, repulsion of neighbouring individuals and alignment of velocity between neighbours. When designing robot swarms, the controlling dynamics of the robots can be based on these models. In this paper we present such a flocking algorithm endowing flying robots with the capability of self-organized collective manoeuvring. The main new feature of our approach is that we include a term in the velocity alignment part of the equations which is an analogue of the usual frictional force between point-wise bodies. We also introduce a generalized mathematical model of an autonomous flying robot, based on flight field tests. With simulations, we test the flocking algorithm from the aspects of the most general deficiencies of robotic systems, such as time delay, locality of the communication and inaccuracy of the sensors. Some of these deficiencies often cause instabilities and oscillations in the system. We show that the instabilities can be efficiently reduced in all states of the system by the inclusion of the friction-like velocity alignment, resulting in stable flocking flight of the robots.
Flocking algorithm for autonomous flying robots
Csaba Virágh, Gábor Vásárhelyi, Norbert Tarcai, Tamás Szörényi, Gergő Somorjai, Tamás Nepusz, Tamás Vicsek