Unmanned aerial vehicles cooperative path planning for ground target tracking via chemical reaction optimization

Abstract

Recent advance in computer science and electronics has greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both military and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. In this paper, we investigate the problem of tracking ground moving object from a group of UAVs using body-fixed sensors under flight dynamical and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO). The efficiency of the proposed was demonstrated through a series of comparative simulations. Experimental results show that the cooperative flyable paths determined by the new method allow for longer sensor coverage time under flight dynamical and safety conditions.