Distributed Cooperative Search Method for Multi-Uav with Unstable Communications

In search-attack and search-rescue tasks performed by multi-UAV, cooperative search plays an important part. The majority of approaches in use today assume that the UAV swarm's communication network is complete. However, these links are susceptible to environmental changes or adversary interference. Aiming at cooperative search in search-attack and search-rescue tasks, we propose a distributed cooperative search method for multi-UAV with unstable communications (DCS-UC), which is developed based on ant colony optimization (ACO). In this method, three algorithms are presented to enable the UAV swarm to conduct online cooperative search efficiently and safely. Firstly, an algorithm of pheromone matrix consensus update used in ACO is designed under switching and connected topology graphs, which can make the pheromone matrix maintained by each UAV achieve consensus, so that the cooperative efficiency of the UAV swarm is improved. Then, a position consensus update algorithm is presented where the position vector, including the positions of all the UAVs in each UAV, can achieve consensus under switching and connected topology graphs. Finally, to tackle the collision avoidance of all the UAVs, an algorithm of collision avoidance between UAVs is designed by using the obtained consistent positions of all the UAVs, which can make the UAV swarm conduct cooperative search safely. Extensive physical simulation results carried out in Gazebo verify the advantages of our multi-UAV cooperative search method.