Author: Nikolaus Feith

image_pdfimage_print

Meta Quest 3

Nikolaus Feith research_robots

Meta Quest 3: Immersive Mixed Reality Headset

Meta Quest 3 is a cutting-edge mixed reality headset designed to blend immersive VR experiences with real-world awareness. Featuring a sleek, ergonomic design, it delivers high-resolution visuals and enhanced comfort, making it ideal for extended use across gaming, productivity, and creative applications.

The headset offers improved performance with advanced optics, a powerful Snapdragon XR2 Gen 2 chipset, and intuitive controls. Its wireless design ensures freedom of movement, while an adjustable fit provides a comfortable experience for all users.

Advanced Mixed Reality Capabilities

Meta Quest 3 integrates full-color passthrough and precise spatial mapping, enabling seamless transitions between virtual and physical environments. Its dynamic sensor suite tracks movement with precision, offering enhanced interaction and immersive AR overlays.

Paired with intuitive hand tracking, haptic controllers, and a robust content ecosystem, Meta Quest 3 redefines how users interact with digital and physical spaces, creating a versatile platform for both entertainment and productivity.

Videos

  • Research videos using the robot will be presented here. 
 

Publications

Sorry, no publications matched your criteria.

Microsoft Hololens 2

Nikolaus Feith research_robots

HoloLens 2: Advanced Mixed Reality Headset

HoloLens 2 is a state-of-the-art mixed reality headset designed to enhance interaction, visualization, and control in various applications. With its ergonomic design and untethered operation, it offers an immersive AR experience, enabling seamless integration of virtual content into the real world.

The device features a high-resolution display with a wide field of view, advanced hand tracking, and eye-tracking capabilities for natural and intuitive interaction. Its lightweight, comfortable fit allows for extended use in diverse environments.

Real-Time Spatial Awareness

HoloLens 2 employs sophisticated spatial mapping and environmental awareness, enabling precise alignment of holographic content with the physical world. Its sensors and depth cameras deliver accurate 3D spatial understanding, making it ideal for simulation, visualization, and control tasks.

With voice commands, gesture recognition, and compatibility with industry-leading software, HoloLens 2 transforms workflows by providing hands-free operation and actionable insights in real time.

Videos

  • Research videos using the robot will be presented here. 
 

Publications

Sorry, no publications matched your criteria.

How to setup ROS2 in PyCharm

Nikolaus Feith wiki_hard_software, wiki_technician

Basic Usage of ROS2 with PyCharm

To access code completion and syntax error handling (debugging doesn’t work in PyCharm directly) in PyCharm for ROS2 the paths have to be linked in your project structure. To do so the following steps have to be performed:

Go to Settings -> Project: <Your-Project> -> Project Structure and Click on Add Content Root.
Now add the two directories: /opt/ros/<your-ros-distro>/lib/<python-version>/site-packages and /opt/ros/<your-ros-distro>/local/lib/<python-version>/dist-packages and set them to Resources

Now the code completion and syntax error handling works for ROS2.

Custom Messages & Custom Packages

To resolve import errors and add code completion in PyCharm for ROS2 projects you have to further set some directories as source roots.

First for custom messages (now called interfaces) build your project once with colcon build. Then go to install -> <name-of-msg-package> -> local -> lib -> <python-version> -> dist-packages and mark this folder as Source with the right click drop down menue. 

For custom packages you go to install -> <name-of-ros2-package> -> lib -> <python-version> -> site-packages and mark this as Source with the right click drop down menue.

Don’t forget the build your project with colcon build if you change your custom packages/modules so the code is updated in the install directory.

Custom Packages and setup.py

To use custom packages in your ROS2 nodes you need to link them in your setup.py file of your ROS2 package. To do so all packages need to have a __init__.py file depending on your package this file is in general empty. Then you open the setup.py file and add all your packages to the list “packages”. The list should look like this: 

packages = [package_name, package_name + ‘/Your_Package’, package_name+’/Your_2nd_Package’],

Use colcon build to update your install directory.

M.Sc. Thesis – Christopher Martin Shimmin: Bayesian Optimization for learning optimal parameters of Electronic Control Units (ECU’s) for Motorcycles

Nikolaus Feith notes_niko, teaching_pastthesestopics

Supervisor: DI Nikolaus Feith;
Univ.-Prof. Dr Elmar Rückert
Start date: 15th Februar 2023

 

Theoretical difficulty: mid
Practical difficulty: mid

Abstract

In the last decade, MotoGP has taken data analytics and telemetrics to a whole new level which has aided in the development and manufacturing of the motorcycles prototypes and their performance on the track.

However, as in other high-end motorsports competitions such as F1, the technological gap keeps getting smaller and, with so, the real potential advantage is gained during testing by trying to find the optimal setup for that specific track and weather conditions. Due to regulations, time dedicated to testing on track is quite scarce, therefore teams and pilots have to find their way around new prototype setups every week to optimize and extract the best performance of the bike.

The main goal of this project is to develop a Bayesian Optimization algorithm that can aid in the fine tuning of ECU parameters of the motorcycle (fuel injection timing and spark ignition timing) while providing a framework and workflow for this methodology.

The work is done in collaboration with the Chair of Cyber-Physical-Systems at Montanuniversitaet Leoben, and Montan Factory Racing, participant of the VII Edition Motostudent Petrol.

Tentative Work Plan

To achieve our objective, the following concrete tasks will be focused on:

  • Literature research
  • Engine and controller model development in Simulink
  • Bayesian optimization algorithm development
  • Hardware integration
  • Testing in practical applications
  • M.Sc. thesis writing and documentation

Related Work

[R1] Isermann, R., Hafner, M. (2001). Mechatronic Combustion Engines – from Modeling to Optimal Control.

[R2] Schillinger, M., Hartmann, B., Skalecki, P., Meister, M., Nguyen-Tuong, D., & Nelles, O. (2017). Safe active learning and safe Bayesian optimization for tuning a PI-controller. IFAC-PapersOnLine, 50(1), 5967-5972.

[R3] Isermann, R. (2014). Engine modeling and control. Berlin: Springers Berlin Heidelberg, 1017.

[R4] Gerhardt, J., Hönninger, H., & Bischof, H. (1998). A new approach to functional and software structure for engine management systems-BOSCH ME7. SAE transactions, 1173-1184.

Thesis

Bayesian Optimization for learning optimal parameters of Electronic Control Units (ECU’s) for Motorcycles

 

Meeting on the 23th, November 2022

Nikolaus Feith notes_niko

Location: Chair of CPS

Date & Time: 23rd Nov 2022

Participants: Univ.-Prof. Dr. Elmar Rueckert, DI Nikolaus Feith, BSc

 

Agenda

  1. Update
  2. Future Steps

Top 1: Update

  • RH8D:
    • Finished the hardware interface, no more communication issues with the left hand.
    • Sample Position controller
  •  Webserver:
    • basics in websockets and js/css/html try outs
    • established connection with ROS2 via rosbridge
    • literature research on related work (shared control, webservers in robotics)
    • search for libraries to display dynamic plots (flot.js or dc.js)

Top 2: Future Steps

  •  

Meeting on the 16th, November 2022

Nikolaus Feith notes_niko

Location: Chair of CPS

Date & Time: 5th Oct 2022

Participants: Univ.-Prof. Dr. Elmar Rueckert, DI Nikolaus Feith, BSc

 

Agenda

  1. Update
  2. Future Steps

Top 1: Update

  • Literature search on Related work to Online Reinforcement Learning and Preference Learning was started
  •  Hardware interface for RH8D was implemented and needs to be tested now. Some issues with exceeding cycle time of the mainloop were found.

Top 2: Future Steps

  • Start working on webservices and ROS2
  • MP:
    • What do we need for kinestetic teaching, shared control etc.
    • Whiech Parameters are changed and how to display them
  • Start with simulation and not a real robot
  • GNN: for the future reimplementation of toy tasks and research whats new in this field or what is still left out
  •  RH8D: Try fixing the communication error with Vedant’s SDK
  • Webserver/Websockets:
    • What are requirements for the webserver/websocket to use it with ROS2 and shared control

Meeting on the 19th, October 2022

Nikolaus Feith notes_niko

Location: Chair of CPS

Date & Time: 5th Oct 2022

Participants: Univ.-Prof. Dr. Elmar Rueckert, DI Nikolaus Feith, BSc

 

Agenda

  1. Update
  2. Future Steps/News

Top 1: Update

  • Since October 12, two presentations were prepared and one was given to the chair on the ROS2 tutorial. The second one deals with the paper “VisuoSpatial Foresigt for Multi-Step, Multi-Task Fabric Manipulation” and will be given next Thursday.
  • Furthermore, a concept for the CPS HUB for the ROS2 repositories was developed and finalized with the other PhD students. 
  • Literature search on Related work to GNN in Motion Planning has been started.
  •  First ROS2 submodule of RH8D robot arm was completed. Data of force sensors at fingertips can be published.

Top 2: Future Steps/News

  • Usage of the desk app in nexttcloud was discussed
  • ROS2: Further discussion on the shared control project, usage of the tablet with android app. Continue working on the RH8D hand.
  • Topics for the Integrated Project, Bachelor’s theses and Master’s theses should be considered. What should be investigated in more detail?
  • Not only on shared control should be further investigated but also GNN.

Introduction to Python

Nikolaus Feith teaching_digicomp, wiki_schueler, wiki_undergradsgrads

Slides by CPS on Python

Short introduction to Python with some first examples and a coding convention. 

Why should you consider learning Python

  • Python is the most popular programming language in the world with a popularity of 28%.
  • It is easier to learn than many other programming languages.
  • Python is very readable due to its structure. Thus, bugs can usually be found and fixed quickly.
  • Python can be both procedural and object-oriented, which makes it very versatile.
  • There is a large number of software libraries. On python package index, PyPI, over 400,000 packages can be found. And the most important ones can be downloaded quickly and easily using pip.
  • Python and almost all Python software libraries are available for free on the Internet.
https://de.statista.com/statistik/daten/studie/678732/umfrage/beliebteste-programmiersprachen-weltweit-laut-pypl-index/

What Python can be used for

  • Data Science is one of the most popular application areas of Python. Here, not only the complete data analysis but also the visualization will be implemented in Python. Generally, software libraries such as Numpy, Matplotlib and Pandas are used for this purpose.
  • Machine learning is another very popular area. Python can be used for supervised, unsupervised and reinforcement learning. Libraries such as TensorFlow, Keras, PyTorch or scikit-learn are used for this purpose.

Furthermore, Python can be used for all kinds of general purpose programs, such as app development, GUI design, web development and in many other areas. In addition, programs with Python interfaces can be automated through a Python program, for example simulation programs.

Practical example of Python in academia

Especially during the time as a student it is good to have a tool with which you can validate your hypotheses or perform the calculations by the computer. Thus, programs can be written with which problems in physics, chemistry or other tasks can be simulated and subsequently the simulation data can be plotted or even videos can be generated.

Important links