A swarm Unmanned Aerial Vehicle (UAV) or quad copter robot for object localization and tracking has been developed. The robot is potentially utilized for military purpose, i.e. doing patrol continuously especially in frontier area. In other words, the UAV is proposed to carry out patrol and exploration by exploring coverage area, find, localize and track suspicious objects. The swarm robots are equipped with Modified Particle Swarm Optimization (PSO) Algorithm for intelligent feature. PSO is an optimization algorithm where each agent of swarm will use its individual perception (local base) and community perception (global base). This swarm quad copter system was implemented using Robot Operating System (ROS) Framework. Experiment was conducted with 3 quadcopter agents and one object as the target. Two main scenarios have been exercised, i.e. a scenario with steady target and another one with moving target. Experimental result shows that Modified PSO implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.