This paper presents a teleoperation system for service robots that integrates human pose estimation with virtual reality (VR) to enable intuitive remote control. By using the Mediapipe framework for 2D pose detection and extending it with RGB-D data from the Intel RealSense D455 camera, a comprehensive 3D human pose estimation is achieved. This data is then mapped to the robot's kinematics, allowing the operator to control the robot's movements naturally. A VR interface was developed to provide an immersive perspective, enhancing the operator's situational awareness. Real-world experiments were conducted using the CHARMIE service robot to validate the system's effectiveness in tasks involving object manipulation. While the current system successfully demonstrates the potential of VR-based teleoperation, challenges remain in accurately capturing certain joint angles (e.g., wrist yaw) and ensuring precise mapping between human and robot movements. Future work includes the integration of inertial measurement units (IMUs) for improved rotational tracking and the implementation of more advanced control algorithms. Overall, this research contributes to the development of more intuitive and effective teleoperation systems for service robots, facilitating their deployment in complex and dynamic environments. This work further introduces a novel approach to teleoperation by combining RGB-D sensing with an innovative algorithm for real-time joint angle computation using Mediapipe, enhancing the precision of human-robot motion mapping and enabling immersive control through a VR interface. These contributions represent significant advancements in the field of human-robot interaction, particularly for service robot applications.

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