Masterarbeit | Mobile Robotics Research Group — Prof. Dr. Christian Pfitzner

Commissioning and HMI Development for the Reachy Mini at TTZ Nürnberger Land

Tue, 09 Jun 2026 00:00:00 +0000

Motivation

The Reachy Mini is one of the most accessible open-source platforms for exploring human-robot interaction. Its compact form factor, expressive head movement, and multimodal sensing (camera, microphones, speaker, antennas) make it ideal for studies and demonstrations where intuitive human-machine communication is at the forefront.

At TTZ Nürnberger Land, it is intended to serve as a lively research and demonstration platform — for technology presentations, visitor interaction, and experimental HRI research.

Work Packages

Commissioning

Assembly and setup of the hardware (Reachy Mini Wireless)
Installation and configuration of the software environment (Python, web dashboard)
Exploration of available APIs, Hugging Face Spaces, and development interfaces

Application Development

Selection and elaboration of a concrete HMI application scenario
Implementation of the interaction logic (speech, gesture, facial expression, camera feedback)
Integration of AI components (e.g. speech recognition, face detection)

Evaluation & Documentation

User study or structured evaluation of the developed application
Documentation of the system as a basis for follow-up projects at TTZ

Requirements

Basic knowledge of Python
Interest in human-robot interaction, AI, or service robotics
Creativity in designing interaction scenarios
Ideally, first experience with embedded systems, Raspberry Pi, or ROS

Depending on the focus and scope, the topic can be carried out as a project thesis, bachelor’s thesis, or master’s thesis.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Location: TTZ Nürnberger Land / TH Nürnberg Georg Simon Ohm

Emergent Systems in Production

Tue, 09 Jun 2026 00:00:00 +0000

Project Description

This 3-semester M-APR project (starting WiSe 2026/2027) compares centralised and decentralised coordination strategies for heterogeneous robot fleets in simulated and real production scenarios. The scientific contribution lies in the empirical characterisation of the transition between both coordination paradigms under varied adversarial conditions.

Structure over Three Semesters

Semester 1 — Foundations and Simulation

Literature review on decentralised coordination and multi-agent reinforcement learning
Building the ROS 2-based simulation environment (at least two agent types: mobile and stationary)
Implementation of a centralised baseline and a simple decentralised approach

Semester 2 — Comparative Study and Learning-Based Coordination

Implementation of learning-based decentralised coordination (MARL)
Systematic comparison under varied adversarial conditions (communication failure, machine failure, dynamic order changes)
Statistical evaluation and identification of transition points between coordination regimes

Semester 3 — Validation and Publication

Transfer of selected scenarios to real hardware at TTZ
Evaluation of sim-to-real transferability
Completion of master’s thesis and preparation of a conference publication (MAPR conference)

Requirements

Bachelor’s degree in electrical engineering, computer science, mechatronics, robotics or equivalent
Programming in C++ and/or Python
Basic knowledge of machine learning / reinforcement learning
Experience with ROS 2 and simulation (Gazebo or similar) is an advantage
Interest in multi-agent systems and production robotics

This topic can also be completed as a project or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de
Co-Supervisor	Waldemar Haag	waldemar.haag@th-nuernberg.de

Location: TTZ Nürnberger Land, Lauf an der Pegnitz

Further information: TTZ Nürnberger Land · Mobile Robotics Lab

Recommissioning of a Mobile C-Arm Robot with Mecanum Drive

Tue, 09 Jun 2026 00:00:00 +0000

Work Packages

Analysis and documentation of the existing robotic system
Review and evaluation of hardware and software components
Troubleshooting and development of a recommissioning concept
Implementation or adaptation of the mecanum drive control
Minor mechanical modifications and integration work
Testing, validation, and documentation of system functionality

Requirements

Interest in mobile robotics, mechatronics, and technical systems
Basic knowledge of robotics, control engineering, or vehicle systems
Practical experience in at least one of the following areas: programming, electronics, or CAD / mechanical design
Ideally, first experience with ROS, Python, or C++
Independent and structured way of working

Depending on the specific focus, the topic can be carried out as a project thesis, bachelor’s thesis, or master’s thesis.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Location: TH Nürnberg Georg Simon Ohm / OIC

2R Robot Arm Lab Experiment – Gravity Compensation and Reinforcement Learning

Mon, 08 Jun 2026 00:00:00 +0000

Motivation

The “Intelligent Robotics” practical course in the M-IAS master’s programme currently lacks a hands-on experiment bridging classical model-based control and modern learning-based methods. A 2R robot arm with torque control offers exactly this: students first experience the physical effects of gravity on the real system, then learn how an RL agent solves the same task in a data-driven way.

Work Packages

Hardware

Selection and commissioning of BLDC motors and motor drivers (e.g. ODrive / VESC)
Mechanical design and fabrication of arm segments (CAD, 3D printing or aluminium profile)
Integration of encoders and wiring

Software & Control

Implementation of forward and inverse kinematics
Model-based gravity compensation controller (real-time torque compensation)
ROS integration: topics, services and ros2_control

Reinforcement Learning

Building a simulation environment (Gazebo or MuJoCo) for RL training
Training an agent (e.g. PPO / SAC) on a target-reaching task
Sim-to-real transfer and evaluation on the real arm

Documentation

Creating lab instructions for use in the M-IAS practical course

Requirements

Knowledge of control theory and robotics (kinematics, dynamics)
Programming skills in Python and/or C++
Ideally experience with ROS
Interest in machine learning and reinforcement learning
Enthusiasm for hands-on hardware work and prototyping

This topic can be completed as a project or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Drone Charging Setup – Automated Wireless Charging of Micro-Drones

Mon, 08 Jun 2026 00:00:00 +0000

Work Packages

Familiarisation with the drone platform and available charging infrastructure
Development of precise approach and landing planning for the charging pads
Mechanical adaptation and fabrication of components (3D printing)
Integration of the charging infrastructure into the automated workflow
Test and evaluation of the charging setup in the flight space

Requirements

Programming skills in Python and/or C++
Experience or interest in mechanical design, CAD or prototyping
Enthusiasm for hands-on hardware work and building prototypes

This topic can be completed as a project, bachelor’s or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Drone Light Painting – Coordinated Light Image Generation with Micro-Drones

Mon, 08 Jun 2026 00:00:00 +0000

Work Packages

Familiarisation with the drone platform and its programming interface
Design and implementation of flight paths for various light patterns
Coordination and synchronisation of multiple drones in the swarm
Experimental testing and photographic documentation of the light images

Requirements

Good programming skills in Python
Interest in autonomous flight and multi-robot systems
Basic understanding of coordinate systems and spatial geometry

This topic can be completed as a project, bachelor’s or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Drone Swarm Obstacle Avoidance – Collision-Free Navigation of Micro-Drones

Mon, 08 Jun 2026 00:00:00 +0000

Work Packages

Integration and calibration of the external 3D camera
Processing, filtering and transformation of point cloud data
Development of a classification to distinguish between persons and drones
Design and implementation of a reactive swarm behaviour with safety zones
Test and evaluation in the flight space with real persons

Requirements

Programming skills (Python and/or C++)
Ideally some experience with ROS
Interest in sensor integration, point cloud processing and perception methods

This topic can be completed as a project or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de

Handling of Flexible Materials Using Robot Arms

Mon, 08 Jun 2026 00:00:00 +0000

Project Description

This 3-semester M-APR project (starting WiSe 2026/2027) addresses the handling of flexible materials by robot arms. The exact focus is agreed jointly and can cover hardware aspects (gripping technologies) or software/AI aspects (simulation, learning-based control). The work concludes with implementation in a real robot cell at the TTZ Nürnberger Land.

Possible Focus Areas

Hardware-oriented

Analysis of gripping principles for flexible materials (vacuum, adhesive, form-adaptive)
Development and fabrication of a specialised gripper
Experimental evaluation of reproducibility

Software / AI-oriented

Building a simulation environment for deformable objects
Model-based control or Deep Reinforcement Learning (DRL)
Vision-Language-Action (VLA) models for flexible manipulation
Sim-to-real transfer and evaluation in the robot cell

Requirements

Bachelor’s degree in electrical engineering, computer science, mechatronics, robotics or equivalent
Programming in C++ and/or Python
Basic knowledge of machine learning
Basic knowledge of robotics
Interest in flexible material handling
Independent and goal-oriented working style
Willingness to engage with new topics

This topic can also be completed as a project or master’s thesis subject to agreement.

Supervision

Role	Name	E-Mail
Supervisor	Prof. Dr. Christian Pfitzner	christian.pfitzner@th-nuernberg.de
Co-Supervisor	M. Sc. Patrick Fußy	patrick.fussy@th-nuernberg.de

Location: TTZ Nürnberger Land, Martin-Luther-Straße 18, Lauf an der Pegnitz

Further information: TTZ Nürnberger Land · Mobile Robotics Lab