Multi-UAV surveillance implementation under hierarchical dynamic task scheduling architecture

In this paper, we consider a multi-UAV surveillance scenario where a team of unmanned aerial vehicles (UAVs) synchronously covers an area for monitoring the ground conditions. In this scenario, we adopt the leader-follower control mode and propose a modified Lyapunov guidance vector field (LGVF) approach for improving the precision of surveillance trajectory tracking. Then, in order to adopt to poor communication conditions, we propose a prediction-based synchronization method for keeping the formation consistently. Moreover, in order to adapt the multi-UAV system to dynamic and uncertain environment, this paper proposes a hierarchical dynamic task scheduling architecture. In this architecture, we firstly classify all the algorithms that perform tasks according to their functions, and then modularize the algorithms based on plugin technology. Afterwards, integrating the behavior model and plugin technique, this paper designs a three-layer control flow, which can efficiently achieve dynamic task scheduling. In order to verify the effectiveness of our architecture, we consider a multi-UAV traffic monitoring scenario and design several cases to demonstrate the online adjustment from three levels, respectively.