Simulation of intelligent Unmanned Aerial Vehicle (UAV) For military surveillance

TLDR

Unmanned Aerial Vehicles are increasingly used in military and security operations for tasks such as surveillance, forestry monitoring, and enemy reconnaissance. This study develops a simulation to model war‑zone conditions for enemy surveillance using UAVs. The system employs a Parrot AR‑2.0 mini quadrotor controlled via ROS, using Adaboost classification and a pinhole algorithm to detect and localize objects. The simulation achieved an average localization error of only 0.24 m across all scenarios.

Abstract

Nowadays, Unmanned Aerial Vehicle (UAV) is an important technology for military and security application. Various missions can be done using UAV such as surveillance in unknown areas, forestry conservation, and spying enemy territory. Application which is developed in this research has a purpose to simulate condition in war zone for spying the enemy. Platform used in the experiment is Parrot AR. Drone ver.2.0, an mini quadrotor which was developed by Parrot SA. This quadrotor controlled by Robot Operating System (ROS) framework. The quadrotor will search and recognize some objects and locate their location. Many algorithms were used to do the mission. To recognize object Adaboost Classifier and Pinhole Algorithm were used. The result shows that average error for all scenario is only 0.24 meters.