Abstract
Recent advances in computer science and electronics have greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both defense 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. This paper investigates the problem of tracking ground moving objects with a group of UAVs using gimbaled sensors under flight dynamic 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 method was demonstrated through a series of comparative simulations. The results show that the cooperative tracking paths determined by the newly developed method allows for longer sensor coverage time under flight dynamic restrictions and safety conditions.
Highlights
Unmanned aerial vehicles (UAV) have been widely used in both defense and civilian applications
We present a solution to the problem of tracking by multiple coordinated unmanned aerial vehicles (UAV) based on the concept of the Receding Horizon Control (RHC) method, which minimizes the uncertainties arising from the application environment and the motion of the target
Tracking moving targets using UAVs is a challenging task due to the uncertainties arising from the Tracking motion ofmoving the target and the UAVs environmental features
Summary
Unmanned aerial vehicles (UAV) have been widely used in both defense and civilian applications. In many of these applications, the UAV is required to continuously track a moving target, such as in the surveillance and tracking of ground objects. This task becomes challenging when the target is moving in a complex and dynamic environment, where the target may be occluded by ground features, such as buildings and mountains. The methods to coordinate the movements of multiple UAVs can be generally grouped into two categories, namely centralized and distributed algorithms, respectively [1].
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