Multi-UAVs collaborative tracking of moving target with maximized visibility in urban environment

Abstract

Unmanned aerial vehicles (UAVs) with limited field of view are utilized to track a moving ground target continuously in urban environment. In urban environment, the sight lines of UAVs to the target are easily blocked by dense obstacles. To overcome this difficulty, the model predictive control (MPC) based collaborative tracking control is proposed with the goal of the maximum visibility of target. First, a visible probability based performance index is proposed, and the flight planning strategy of maximum the phase difference is obtained as a consequence. Then a centralized MPC based collaborative control problem is solved to obtain the optimal control signals. The joint cost function consists of four parts which aims at tracking target, avoiding collision, avoiding the blind area and maintaining the maximum visibility, respectively. The effectiveness of the proposed collaborative strategy is verified by simulation. Compared with the traditional MPC-based collaborative method, the proposed maximum visible probability index provides an optimal dynamic formation structure for multi UAVs to guarantee the tracking of the moving ground target in urban environment.