Modular Swarm UAV-aided Data Collection for WSNs relying on Cooperative Communication and Path Planning

Using Swarm UAVs to collect feedback information from sensor nodes can greatly improve the coverage rate and energy efficiency of Wireless Sensor Networks (WSNs), especially for environmental monitoring in inaccessible areas. Based on a modular swarm UAV platform and randomly distributed sensor network, this paper devotes to design a clustering algorithm which considers the distance constraints of sensor communication. Then, relying on the cluster results, we propose an Ant Colony Optimization (ACO)-based cooperative path planning for modular UAVs, with multiple constraints brought by characters of separate/recombine modes. Simulation results indicate that the proposed clustering algorithm and cooperative path planning is capable of effectively realizing the adaptive clustering and improving the total information collected by the UAV-aided WSNs.