Handling of Flexible Materials Using Robot Arms
Abstract
Flexible materials such as films, textiles, plastics, cables or limp components are gaining increasing importance across many industries — in automotive and electronics manufacturing, the packaging industry, and medical technology applications. Their specific material properties enable cost-effective and functional products. With rising production automation, reliable and precise handling of these materials is becoming a key challenge, as conventional robot systems are primarily designed for rigid workpieces.
The focus of the thesis will be defined in consultation with the student and can follow personal interests. Possible directions include:
Hardware: Development of specialised gripping technologies that flexibly adapt to material compliance and enable reproducible manipulation.
Software / AI: Methods for handling the non-linear, highly deformable and hard-to-predict behaviour of flexible materials, e.g. advanced simulation, model-based control or AI-based approaches (Deep Reinforcement Learning, Vision-Language-Action models).
The work concludes with implementation and evaluation in a physical robot cell at the TTZ Nürnberger Land.
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 | |
|---|---|---|
| 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
Prof. Dr. Christian Pfitzner
Professor of Mobile Robotics
Professor of Mobile Robotics at TH Nürnberg Georg Simon Ohm, Faculty efi. Director of the TTZ Nürnberger Land. Research interests in autonomous navigation, drone technology and sensor fusion.