Distributed anti-flocking method for area coverage of multiple unmanned aerial vehicles

The area coverage problem is an important issue because it can minimize uncertainty in a complex and unknown environment. This paper adopts a distributed anti-flocking algorithm inspired by the social behavior of solitary animals, which enables self-organized collaboration of multiple unmanned aerial vehicles (multi-UAVs) to achieve effective coverage of the mission area. The designed area coverage map represents the historical coverage information of each unmanned aerial vehicle (UAV). According to the rules of collision avoidance, decentering, and selfishness in the distributed anti-flocking algorithm, the UAVs are guided to move towards the direction that maximizing the coverage area and try to reduce the overlap of coverage region as well. Simulations show that the algorithm can achieve approximate full coverage of the task area and has good scalability, adaptability, and robustness.