Flock properties effect on task assignment and formation flying of cooperating unmanned aerial vehicles

Abstract

In this article, a hierarchical algorithm was developed for autonomous formation flying, communication, and task assignment for cooperating unmanned aerial vehicles (UAVs) and Dudek's taxonomy was used to evaluate the performance of the autonomous UAV group cooperating in mission execution against a group of enemy agents in an unknown environment. The authors showed that increasing the number of UAVs in the group proves to be beneficial as it allows the group to react to more enemy events, even if the overall search and detect capabilities remain invariant with the number of UAVs. It is also showed that, in general, using communication improves the cooperation among the flock members; however, using infinite communication range or infinite communication bandwidth results in considerable computational complexity. In conclusion, it is sufficient to use finite-bandwidth communication, keeping the computational complexity constant with the number of UAVs in the group, thus allowing the group to be scalable to large numbers of UAVs. The authors use a behavioural flocking algorithm to control the movement of the UAVs when searching, and show that flocking assists the UAVs in dispersing in the environment and improves the overall detection probability of the flock. Finally, it is showed that using flocking improves the group performance only if the group is capable of mission task collaboration.