Unser Lehrling Kosmo Obermayer berichtet über seinen Lehrberuf als Informationstechnologe mit Betriebstechnik und gibt spannnende Einblicke in seinen Alltag am Lehrstuhl für Cyber-Physical-Systems.

Der Artikel ist unter diesem Link erreichbar.

Are you fascinated by the intricate dance of robots and objects? Do you dream of pushing the boundaries of robotic manipulation? If so, this internship is your chance to dive into the heart of robotic innovation!

You can work on this project either by doing a B.Sc or M.Sc. thesis or an internship.

Job Description

This internship offers a unique opportunity to explore the exciting world of robotic learning. You’ll join our team, working alongside cutting-edge robots like the UR3 and Franka Emika cobots, and advanced grippers like the 2F Adaptive Gripper (Robotiq), the dexterous RH8D Seed Robotics Hand and the LEAP hand. Equipped with tactile sensors, you’ll delve into the world of grasping, manipulation, and interaction with diverse objects using Deep Learning methods.

Start date: Open

Location: Leoben

Duration: 3-6 months

Supervisors:

• Fotios Lygerakis
  
• Univ. Prof. Dr Elmar Rückert

Keywords:

• Robot learning
• Robotic manipulation
• Reinforcement Learning
• Sim2Real
• Robot Teleoperation
• Imitation Learning
• Deep learning
• Research

Responsibilities

• Collaborate with researchers to develop and implement novel robotic manipulation learning algorithms in simulation and in real-world.
• Gain hands-on experience programming and controlling robots like the UR3 and Franka Emika cobots.
• Experiment with various grippers like the 2F Adaptive Gripper, the RH8D Seed Robotics Hand and the LEAP hand, exploring their functionalities.
• Develop data fusion methods for vision and tactile sensing.
• Participate in research activities, including data collection, analysis, and documentation.
• Contribute to the development of presentations and reports to effectively communicate research findings.

Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science,
  Electrical Engineering, Mechanical Engineering, Mathematics or related
  fields.
• Solid foundation in robotics fundamentals (kinematics, dynamics, control theory).
• Solid foundation in machine learning concepts (e.g., supervised learning, unsupervised learning, reinforcement learning, neural networks, etc)
• Strong programming skills in Python and experience with deep learning frameworks such as PyTorch or TensorFlow.
• Excellent analytical and problem-solving skills.
• Effective communication and collaboration skills to work seamlessly within the research team.
• Good written and verbal communication skills in English.
• (optional) Prior experience in robot systems and published work.

Opportunities and Benefits of the Internship

• Gain invaluable hands-on experience with state-of-the-art robots and grippers.
• Work alongside other researchers at the forefront of robot learning.
• Develop your skills in representation learning, reinforcement learning, robot learning and robotics.
• Contribute to novel research that advances the capabilities of robotic manipulation.
• Build your resume and gain experience in a dynamic and exciting field.
   

Application

Send us your CV accompanied by a letter of motivation at fotios.lygerakis@unileoben.ac.at with the subject: “Internship Application | Robot Learning”

Related Work

• MViTac: Self-Supervised Visual-Tactile Representation Learning via Multimodal Contrastive Training
• M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation

Funding

We will support you during your application for an internship grant. Below we list some relevant grant application details.

CEEPUS grant (European for undergrads and graduates)

Find details on the Central European Exchange Program for University Studies program at https://grants.at/en/ or at https://www.ceepus.info.

In principle, you can apply at any time for a scholarship. However, also your country of origin matters and there exist networks of several countries that have their own contingent.

Ernst Mach Grant (Worldwide for PhDs and Seniors)

Find details on the program at https://grants.at/en/ or at https://oead.at/en/to-austria/grants-and-scholarships/ernst-mach-grant.

Rest Funding Resourses

Apply online at http://www.scholarships.at/

Supervisor: Univ.-Prof. Dr Elmar Rückert

Project: K1-MET P3.4
Start date: 1st of May 2024

Theoretical difficulty: high
Practical difficulty: mid

Topic

The the steel production, the steel quality heavily depends on the dynamic processes of the meniscus level fluctuations in the mold. These complex dynamic  processes can be observed using IR cameras observing the surface level and the casting powder temperature. 

The goal of this thesis is to develop and compare deep learning approaches (CNNs, transformers) for predicting fluid dynamics in lab prototype environment. 

Tasks

• Literature research of state of the art, see references
• Lab prototype environment for generating complex (structured and chaotic) fluid dynamics
• Dataset recording, visualization and annotation
• Deep Learning algorithm implementation (CNNs & Transformers)
• Evaluation on different datasets (predictable dynamics, complex dynamics, synchronous and async. surface level dynamics, chaotic dynamics).
• Thesis writing.

References

• Enhancing computational fluid dynamics with machine learning R Vinuesa, SL Brunton, Nature Computational Science, 2022.
• Current and emerging deep–learning methods for the simulation of fluid dynamics M Lino, S Fotiadis, AA Bharath… – Proceedings of the …, 2023.
• Unsupervised deep learning of incompressible fluid dynamics, N Wandel, M Weinmann, R Klein, arXiv preprint arXiv:2006.08762, 2020.

Supervisor: Univ.-Prof. Dr Elmar Rückert

Start date: 1st of August 2023

Theoretical difficulty: mid
Practical difficulty: mid

Thema der Arbeit

LEGO Ev3 Robotersysteme werden am Lehrstuhl in der Lehre eingesetzt, um einen einfachen Einstieg in die Robotik zu ermöglichen. Zahlreiche Algorithmen können erprobt werden: 

• Pfadplanung und Navigation
• Kalman Filter
• Kartierung / SLAM
• Objektmanipulation 
• Kamerabasierte Objekterkennung
• Regelungsalgorithmen
• Telemetrieaufgaben
• usw.

Unsere EV3 Systeme sind mit einem Linux Betriebsystem (https://www.ev3dev.org) ausgestattet und können in der Programmiersprache Micro-Python bespielt werden. 

Ziel dieser Arbeit ist es eine Entwicklungsumgebung für die klassische Python Programmiersprache zu schaffen. Dabei sollen Beispielprojekte umgesetzt und Limitierungen dokumentiert werden. 

Aufgaben

• Recherche und Dokumentation zur State-of-the-Art
• Beispielprojekte Implementieren
• Git Repository mit Dokumentation erstellen.
• Dokumentation der Arbeitsschritte & Verfassen der Diplomarbeit

Wissenschaftlicher Beitrag

• Entwicklung und Implementierung einer Entwicklungsumgebung in Python für die Lehre. 
• Veröffentlichung des Source Codes. 

Abschlussarbeit

B.Sc. Thesis by Tanja Sukal on Open-Source LEGO EV3 Python Framework for Teaching, 2024.

Supervisor: Univ.-Prof. Dr Elmar Rückert

Company: Ottronic GmbH
Start date: 1st of October 2023

Theoretical difficulty: mid
Practical difficulty: mid

Thema der Arbeit

Bei Ottronic bildet die Verkapselung unserer Elektroniken und Motoren mittels eines eigens adaptierten Reactive Injection Molding (RIM) Verfahren die Grundlage für die Produktion von medienresistenten Elektroniken und elektrischen Hochleistungsantrieben. Im Zuge des RIM werden sogenannte b-staged Duroplaste unter einem präzisen Druck- und Temperaturprofil verarbeitet, geformt und final ausgehärtet. Um die angestrebte höchste Produktqualität, mit Blick auf Medizintechnik-Applikationen, zu gewährleisten, muss dieser Prozess mit jedem Schuss optimal eingestellt sein. Daher soll ein Cyber Physical System (CPS) entwickelt werden, welches auf unsere RIM-Anlagen nachgerüstet wird.

Ziel der Diplomarbeit ist, dass das finale CPS selbstständig Prozessschwankungen (Chargenschwankungen, Hallen-/Maschinentemperatur, Feuchte, etc.) erkennen kann und Regelparameter des Spritzgussvorgangs (Schmelzzeit, Aushärtezeit, Einpresskraft, etc.) anpassen um eine gleichbleibende Produktqualität ohne menschliche Kontrolle zu garantieren.

Dabei soll in einem ersten Schritt der aktuelle Prozess beschrieben werden. Daraus sollen die notwendigen Produktionsparameter abgeleitet und deren Auswirkungen auf den Prozess analysiert sowie die Kernpunkte zur Prozessoptimierung definiert werden, sowie ein Modell dafür entwickelt werden. Das zu entwickelnde Modell dient dann in weitere Folge als Basis für das CPS um den Prozess zu bewerten zu können, Abweichungen zu detektieren und Regelparameter abzuändern.

In weiterer Folge soll das Modell auf der Maschinensteuerung CPS integriert und implementiert werden. Abschließend muss noch die Verknüpfung der neu gewonnen Intelligenz des CPS mit der aktuellen Regelung der Maschine verknüpft werden um eine nahezu autonome Prozessführung zu garantieren, sowie eine neue ressourcen- als auch energieeffizientere Spritzpressmethode garantieren.

Aufgaben

• Recherche und Dokumentation zur State-of-the-Art
• Erfassung aller notwendigen Produktionsparameter sowie Analyse derer auf Produktqualität
• Entwicklung eines Modelles zur virtuellen Beschreibung des Spitzgussprozesses Implementierung des Modells auf Maschinensteuerung als Basis für ein CPS
• Identifizierungen von Abweichungen im Prozess sowie Implementierung von Gegenmaßnahmen
• Verknüpfung der Prozessregelung mit Steuerungsempfehlungen des CPS.
• Dokumentation der Arbeitsschritte & Verfassen der Diplomarbeit

Wissenschaftlicher Beitrag

• Entwicklung und Implementierung eines CPS, welches einen RIM Prozesses erfassen und abbilden kann.
• Aufbau von Methoden um auf Basis des CPS Änderungen des RIM-Prozesses erkennen und bewerten zu können
• Retrofitting der gewonnen Intelligenz in eine bestehende Maschinensteuerung

Here’s a link to download logos in full resolutions:

https://qm.unileoben.ac.at/en/qm-documents/q4-communication

Put your documents at TravelApplications/drafts

Here: https://cloud.cps.unileoben.ac.at/index.php/f/977844

Create the folder with your name

Travel Planning Checklist

Approval and Registration

• Initial Planning: Check for a reasonable flight itinerary. Check if 1-2 days before and after the event have a substantially lower price. 
• Obtain Approval: Secure trip approval from Elmar. Argue according to the initial planning.
• Travel System Entry: Request Regina to input the trip details into the travel system. Specify which days are for official duties (e.g., conference, lab visits) and which are for personal stay. Provide Regina with the proof of acceptance, or reason to travel.

Booking Essentials

• Accommodation and Commute Options: Provide a comparison spreadsheet of different options within the budget. Opt for reasonable over the cheapest options.
• Booking Approval: Get approved by Elmar.
• Accommodations and Commute: After obtaining approval, book your stay, conference registration, accommodations, etc. 

Travel Insurance

• Carry Insurance Documentation: If traveling abroad, particularly outside the EU, bring a printed copy of the university’s or other relevant insurance policy

Visa Requirements

• Include Embassy Commute: If a visa is necessary, incorporate the embassy commute in the travel system and communicate this to the secretary for travel cost reimbursement.
• Visa Application Time: Visa application efforts are recognized as working hours.

After the Travel

• Receipts: After the end of the trip, provide Regina with all the receipts, invoices, and tickets from:

• • • Airplanes, trains, buses, and boats: tickets, invoices, bank statement
    • Accommodation: invoice, bank statement

• Registrations: invoice, bank statement

• etc.

Important Notes

• OEBB Trains: The chair has a membership with OBB, please book the ticket in the user’s name. You can obtain the user’s login information from Regina.

• After the travel: Keep all original receipts and submit them to Regina after returning.
• Report Everything: Due to Austrian law for work insurance coverage, you must inform Regina by email if you will be outside the university zone during working hours, even for a few hours.
• Private Stay: A private stay cannot exceed 50% of the duration of the working days. For example, if a conference is for six days, your private stay must be a maximum of three days. Otherwise, the university will cover only 50% of the flight tickets and hotel.

Tips:

• Credit card with travel coverage (check if hospitalization is included for overseas)

Here’s a guide on how to label your categories effectively:

1. wiki_phds: This category should encompass all aspects of your day-to-day life as a PhD student.

2. wiki_road_to_thesis: Include guidelines, tips, and resources related to various stages of thesis writing, from proposal development to final defense preparations.

3. wiki_hard_software: Use this category to share information, tutorials, and updates about the hardware and software used in your research projects.

4. wiki_scientific_research_aspects: Discuss methodologies, data analysis techniques, experimental setups, and anything else related to the scientific rigor of your work.

5. wiki_teaching_aspects: This category is dedicated to sharing insights, strategies, and resources for effective teaching, whether it’s leading a seminar, designing a course, or mentoring undergraduates.

6. wiki_career_aspects: This category covers everything related to career development and professional growth.

The category label determines where the post will appear in its respective section.

Date & Location: 24.05.2024 17:00-21:00

We expect many visitors and will prepare some beverages. Please let us know if you plan to join! 

Chair of Cyber-Physical-Systems 
Metallurgiegebäude 1.Stock
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria

https://youtu.be/jLAUo_Kk01E

Impressions of the last open lab day in 2024.  

English: Immerse yourself in the fascinating world of artificial intelligence and robotics. We present self-learning robots, mobile robot guides and how deep neural networks are learned. Children can experiment with our Lego EV3 robots and try to deliver snacks autonomously. Catering will be provided.

Deutsch: Tauchen Sie ein in die faszinierende Welt der künstlichen Intelligenz und Robotik. Wir präsentieren selbstlernende Roboter, mobile Roboterguides und wie tiefe neuronale Netze gelernt werden. Kinder können mit unseren Lego EV3 Robotern experimentieren und versuchen Snacks autonom auszuliefern. Für Verpflegung ist gesorgt.

The pictures above are from October 2023 and will be updated after the event. 

Program