Object Detection and Tracking with Autonomous UAV
This work addresses the problem of autonomous UAV operations for military or surveillance applications, but it appears incremental as it applies existing methods like computer vision and deep learning to a new simulation setup.
The paper tackled the problem of enabling a combat UAV to perform object detection and tracking tasks in a simulation environment, resulting in successful execution of locking on targets, tracking, and data sharing with surrounding vehicles.
In this paper, a combat Unmanned Air Vehicle (UAV) is modeled in the simulation environment. The rotary wing UAV is successfully performed various tasks such as locking on the targets, tracking, and sharing the relevant data with surrounding vehicles. Different software technologies such as API communication, ground control station configuration, autonomous movement algorithms, computer vision, and deep learning are employed.