Hardware-Based Implementation of Target Tracking in Unmanned Aerial Vehicles (UAVs)

Abstract

Unmanned Aerial Vehicles (UAVs) have gained sig-nificant attention in various fields, including surveillance, search and rescue, and monitoring applications. One important application for UAV s is target tracking, which requires detecting and tracking a specific object of interest in real time. This paper surveys work done so far in the area of target-tracking in UAV s. It then presents a comprehensive hardware-based framework for target tracking in UAV s. This work utilizes the State-of-the-Art YOLOv8 (You Only Look Once) algorithm for target detection, an efficient high-speed target tracking model, and a Proportional Derivative (PD) control algorithm for precise drone movement control. YOLOv8 provides fast, accurate, and real-time detection of the object of interest, allowing the UAV to detect and identify the target object quickly and reliably. Subsequently, a robust tracking algorithm tracks the identified object across consecutive frames, ensuring accurate localization and trajectory estimation. Furthermore, a PD control algorithm is integrated into the system to enable precise and smooth drone movement. The proposed framework is integrated and used for target tracking in UAV s. Further, this framework is implemented on a UAV. The results demonstrate the effectiveness and robustness of the proposed framework, showcasing its potential for real-world applications.