The growing demand for efficient and reliable human-robot collaboration (HRC) in industrial environments has driven the integration of Augmented Reality (AR) and real-time robotic control systems. This paper presents an AR-enabled HRC system where operators use Almer Arc2 AR headsets to issue voice commands that control the movement of the xArm 7 robotic arm. The system leverages ROS 2 and MoveIt for motion planning, augmented by a decision tree-based optimization model for trajectory calculation. A key performance metric, response time, is evaluated to assess the system’s efficiency in translating voice commands into precise robotic actions. Experimental results show a mean response time of 1.45 seconds, indicating stable and rapid responses suitable for real-time industrial applications. The system’s accuracy and repeatability were also confirmed, with minimal variations in pick and drop locations, demonstrating high precision in task execution. These findings highlight the system’s potential to enhance workflow efficiency, reduce cognitive load on operators, and ensure seamless interaction between human and robot. By integrating intuitive AR interfaces and real-time feedback, this study contributes to advancing intelligent and adaptable human-robot workspaces for industrial automation.