Rohstoffe 2024

FFG Projekt 15/11/2025-14/11/2028

Ziel des Projekts MineView ist die Entwicklung eines digitalen Überwachungssystems, das letztendlich eine ganzheitliche und kontinuierliche gebirgsmechanische Zustandsbewertung von untertägigen Bauwerken ermöglicht. Durch den Einsatz von Robotern, Sensorik und KI werden bestehende Überwachungsmethoden revolutioniert und eine neue Ära der digitalen Bergwerksüberwachung eingeleitet.

Der Lehrstuhl wird im Zuge dieses Projektes den Einsatz von autonomen Robotern und/ oder Drohnen für die Zustandserfassung und Integration in bestehende Produktionsabläufe erforschen. 

Bild, akustische und andere Daten werden systematisch erfasst und mit maschinellen Lernmethoden ausgewertet. Ziel ist die automatische Erkennung von Mustern in gebirgsmechanischen Daten sowie in Umweltdaten. Die Vorhersagen der entwickelten  Lernmethoden sollen in Frühwarnsystemen kritische Zustände frühzeitig identifizieren und so zur Sicherheit im Untertagebau beitragen.

Projektconsortium

• Montanuniversität Leoben
  • Lehrstuhl für Bergbaukunde, Bergtechnik und Bergwirtschaft (BBK) 
  • Lehrstuhl für Cyber-Physical-Systems (CPS)
• RHI Magnesita

Fördergeber

• Österreichische Forschungsförderungsgesellschaft mbH (FFG)

Schlüsseltechnologien im produktionsnahen Umfeld 2025

FFG Projekt 08/2026-07/2029

Abbildung: Schematische Darstellung existierender Technologien (a bis g), die im industriellen Umfeld engesetzt werden (h). 

Projektconsortium

• Montanuniversität Leoben
  • Forschungs- und Innovationsservice Montanuniversität (Administrativer Koordinator)
  • Lehrstuhl für Automation und Messtechnik
  • Lehrstuhl für Cyber-Physical-Systems
• Knapp AG
• Boehlerit GmbH&Co.KG
• RISKSEN

Fördergeber

• Österreichische Forschungsförderungsgesellschaft mbH (FFG)

Student Assistant at the Montanuniversität Leoben

Short bio: Cynthia Ani joined CPS in March 2026.

She is studying data science in her final year of her masters program at the TU Graz and industrial data science in Leoben. Her research interests includes AI and in particular modern machine learning methods. 

Research Interests

• Data Science
• Machine Learning
• Foundation Models (AI)

Contact

Cynthia Ani
Student Assistant at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria 

Email:cynthia-ugonna.ani@stud.unileoben.ac.at

Student Assistant at the Montanuniversität Leoben

Short bio: Peyman Kahrizi joined CPS in 2026.

He is currently working on his Master’s thesis at Montanuniversität Leoben. His research focuses on real-time dense SLAM using RGB-D sensors, including dense 3D reconstruction with Gaussian Splatting, pose estimation using GICP, and semantic scene representation based on CLIP language embeddings.  His work is implemented primarily in Python using Open3D. 

Research Interests

• 3D Reconstruction
• SLAM
• Pose Estimation
• Machine Learning

Contact

Peyman Kahrizi
Student Assistant at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria 

Email: peyman.kahrizi@stud.unileoben.ac.at

Thank you to the CPS team for a successful year, which we concluded with a delightful Christmas party at the local restaurant Erlsbacher in Leoben.

Secretary

Short bio: Katharina Binder joined the CPS team in November 2025 and is responsible for organizational and administrative matters. She holds a diploma from the International Bilingual Business College in Hetzendorf with a focus on marketing. Before that, she completed her secondary education at the Higher Institute for Tourism in Krems, specializing in tourism management. She also studied political science at the University of Vienna.

Research Interests

• Cyber-Physical-Systems 
• Modern Technologies 
• Learning Machines and Robotics

Contact

Katharina Binder
Sekretariat des Lehrstuhls für Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Phone:  +43 3842 402 – 1901
Email:   sandra.binder@unileoben.ac.at 
Web:  https://cps.unileoben.ac.at

CPS Conveyer Belt System

Our conveyer belt system has a dimension of approx. 5 x 3 meters with 40cm belts. It is used to develop autonomous robotic systems for recycling applications.

Videos

• Research videos using the robot will be presented here. 

Publications

Ph.D. Student at the Montanuniversität Leoben

Short bio: Mr. Guenther Hutter will start at CPS on 1st of September in 2025. 

Günther Hutter is an experienced educator and researcher in the fields of computer science, automation, and cybersecurity. He holds degrees in Software Design and Advanced Security Engineering from the University of Applied Sciences Kapfenberg, both awarded with distinction. His professional background includes leadership roles in software development and PLM integration, with a focus on software architecture, data quality, and industrial IT systems.

Since 2017, he has served as head of the IT & Smart Production division at HTL Leoben, where he is responsible for curriculum development and interdisciplinary laboratory instruction across multiple engineering domains. His teaching and research interests encompass embedded systems, industrial communication, IT security, and open-source educational technologies. As founder of bytebang e.U., he also engages in applied research and consulting in IoT, data visualization, and system integration.

Research Interests

• Machine Learning
• Robotics
• Computer Vision

Contact & Quick Links

Guenther Hutter, M.Sc.
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert.
Montanuniversität Leoben
Roseggerstrasse 11 , 
8700 Leoben, Austria 

Phone:  +43 3842 402 1901
Email:   TBA 
Web Work: CPS-Page
Chat: WEBEX

Personal Website: bytebang.at
GitHub: bytebang
LinkedIn: Günther Hutter

Publications

Meeting Notes

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Ph.D. Student at the Montanuniversität Leoben

Short bio: Mr. Sai Puneeth Reddy Gottam started at CPS on 1st of July in 2025. 

He received his Master degree in Automation and Robotics from RWTH Aachen University in 2024 with the study focus on Robotics and Machine Learning. His thesis was entitled “Adaptive feature tracking in visual odometry using self-supervised learning for
challenging environments”, which took place at Space Application Services NV/SA, Brussels. In the thesis, he implemented Self-supervised learning improving feature detection for Visual Odometry in complex large scale environments. Before that, he also did his Research internship at Space Application Services, where he worked on synthetic data generation and object detection for vessel detection.

Research Interests

• Machine Learning
• Robotics
• Computer Vision
• Humanoids

Contact & Quick Links

M.Sc. Sai Puneeth Reddy Gottam
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert.
Montanuniversität Leoben
Roseggerstrasse 11 , 
8700 Leoben, Austria 

Phone: +43 3842 402 – 1901 (Sekretariat CPS)
Email:   sai.gottam@unileoben.ac.at 
Web Work: CPS-Page
Chat: WEBEX

Personal Website
GitHub
Google Citations
LinkedIn
Research Gate

Publications

Supervisor: Univ.-Prof. Dr Elmar Rückert

Project:§27 Hopbas Pipe
Start date: 1st of May 2024

Theoretical difficulty: low
Practical difficulty: high

Topic

The goal of this project is to develop a webinterface to record a very large number of various sensors, to visualize the data and to store it into a database. 

To connect and transform the sensor data a programmable hardware device, theAdvantech ADAM 6017-D is used. 

Tasks

• Literature research of state of the art, see references
• Lab prototype environment for recording multiple sensors (different bus protocols, analog and digital)
• Dataset recording, visualization
• User interface to add sensors and to start tests
• Evaluation on of different tests (varying number of sensors, ADAM devices, etc.).
• Thesis writing.

References

• TASMOTA
• MQTT
• MODBus

Bachelor Thesis

The final bachelor thesis document can be downloaded here.