LAUSR

The rapid development of Space-Air-Ground integrated network, IoT, and swarm-based robotic systems has promoted the transformation of traditional single drone toward drone swarm. Compared to the traditional single drone, drone swarm can collaboratively complete complex tasks with higher efficiency and lower cost, especially in harsh environments. Communication and networking techniques are essential to enabling collaborate information sharing, coordinating multiple drones, and achieving autonomous drone swarm. However, the traditional communication technologies on fixed networks or slowly moving networks cannot address the unique characteristics of drone swarm, such as high dynamic topology, intermittent links and capability constraints. Two kinds of networking techniques fit for different drone swarm tasks are investigated, and the performance indexes of several wireless technologies suitable for drone swarm are also analyzed. Considering that drone swarm would usually be deployed in dire circumstances and the network may get frequently partitioned, the robustness of drone swarm becomes crucial. Based on the Molloy-Reed criterion, a swarm intelligent robust solution for drone swarm is proposed by using the consensus method and grey prediction, which has advantages of small overhead and local information exchanging. The simulation results corroborate that the robustness to node failure of drone swarm can be effectively improved by the proposed method.