The Tactile Internet (TI) is a new paradigm for remote interactions, enabling the transmission of touch and physical sensations. One of the major challenges in achieving seamless remote interactions is latency. To circumvent strict latency requirements, the paper briefly introduces the approach of a Model Mediated Teleoperation scheme utilizing a locally run physics engine to simulate the remote environment.

The focus of this paper is on solving the problem of tracking objects in TI workspaces, to be able to simulate them.
We developed a pattern recognition-based pose estimation technique using OpenCV's Perspective-n-Point solver, which accurately estimates the pose of objects in real time.
Further contributions include the implementation of a virtual test bed in the Unity game engine. The solver and test bed were integrated with a Python Flask server. This approach proved to be effective in providing accurate position and rotation estimation.