This paper introduces an innovative robotic teleoperation system that combines augmented reality (AR) with a robotic arm to achieve natural human-robot interaction. The system aims to enhance the precision and efficiency of remote operations by providing intuitive visual feedback and seamless integration of virtual and real-world environments. Key components include an AR headset (HoloLens 2) for capturing and overlaying virtual controls, a Franka Emika Panda robotic arm for manipulating objects, and a communication protocol (TCP/IP) for real-time data transfer between the headset and the robotic arm. The system's effectiveness is demonstrated through various experiments, showing low error rates and successful completion of tasks in real-world scenarios. The authors discuss the system's potential applications in medical procedures, industrial settings, and space exploration, while also highlighting limitations such as restricted field of view and object recognition accuracy. Future work will focus on improving these aspects to further enhance the system's practicality and performance.This paper introduces an innovative robotic teleoperation system that combines augmented reality (AR) with a robotic arm to achieve natural human-robot interaction. The system aims to enhance the precision and efficiency of remote operations by providing intuitive visual feedback and seamless integration of virtual and real-world environments. Key components include an AR headset (HoloLens 2) for capturing and overlaying virtual controls, a Franka Emika Panda robotic arm for manipulating objects, and a communication protocol (TCP/IP) for real-time data transfer between the headset and the robotic arm. The system's effectiveness is demonstrated through various experiments, showing low error rates and successful completion of tasks in real-world scenarios. The authors discuss the system's potential applications in medical procedures, industrial settings, and space exploration, while also highlighting limitations such as restricted field of view and object recognition accuracy. Future work will focus on improving these aspects to further enhance the system's practicality and performance.