Pattern-based pose estimation for Tactile Internet

Bachelor Thesis (2023)
Author(s)

M.L.L. Craenen (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Rangarao Venkatesha Prasad – Mentor (TU Delft - Networked Systems)

Herman Kroep – Mentor (TU Delft - Networked Systems)

Michael Weinmann – Graduation committee member (TU Delft - Computer Graphics and Visualisation)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Marijn Craenen
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Marijn Craenen
Graduation Date
28-06-2023
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

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.

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