Grasping Unknown Components for Robotic Assembly

Mon, 07 Sep 2026 00:00:00 +0000

Motivation

Frequent component revisions pose a challenge for industrial assembly processes. With every change cycle, the design, colour and material of a component may change. In robotic assembly, this challenge creates a demand for robots capable of adaptation.

Topic Area

For assembly, the robot system has access to a stored assembly plan. This plan contains the component designations, the assembly sequence and the region, the latter serving to roughly localise the assembly position. In order to assemble components under these boundary conditions, the components at hand must be detected, matched to a component designation and their grasp pose determined. To date, neural networks are trained on already known objects. They are therefore limited with regard to capturing new, unknown components.

Description

The aim of this thesis is to overcome the limitation to previously known objects. An approach for detecting unknown objects and computing their grasp poses is to be developed and subsequently compared with existing approaches.

Adaptability can be achieved by combining visual sensing with methods of artificial intelligence. RGB and depth cameras form the interface between the robotic system and its environment. The resulting image data can be analysed using methods of artificial intelligence, e.g. neural networks, in order to detect and then grasp unknown components.

For practical validation of the findings, a robot cell with a collaborative robot from Universal Robots at the Technology Transfer Centre Nürnberger Land in Lauf is available.

Requirements

Programming skills (preferably Python and/or C++)
Ideally initial experience with ROS and neural networks
Interest in robotics and deep learning

This topic is suitable for a bachelor’s, project or master’s thesis and can also be combined with further topics for an M-APR.

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

Handling of Films and Paper Interlayers

Mon, 07 Sep 2026 00:00:00 +0000

Motivation

Metal components are coated with a film of oil for corrosion protection. This oil film contaminates the containers used for transport. In order to reduce contamination and the associated cleaning effort, films are used as interlayers. They separate the oily components from the container.

Topic Area

Placing the interlayers is challenging due to the flexibility of the thin films and paper layers. Correct placement of the interlayers is essential. This requires deliberate folding in order to adapt the interlayer to the box. During the process, unintended folds of the interlayer may occur. These have to be unfolded so that the interlayer can be placed flat. A further challenge, particularly with films, is the electrostatic adhesion of the film surfaces. The adhering film surfaces have to be separated again by the robot.

Description

The aim of this thesis is to develop a concept for placing interlayers into a box and to compare it with existing approaches. The interlayer is to be grasped and prepared for placement into the box. This includes unfolding it and adapting it to the box. The robot should then insert the interlayer and verify its correct positioning.

In a first stage, a concept for a paper interlayer is to be developed. This is subsequently transferred to plastic films. Robot cells with collaborative robots from Universal Robots are available for validation. Experiments to validate the concept can be carried out at the Technology Transfer Centre Nürnberger Land in Lauf.

Requirements

Programming skills (preferably Python and/or C++)
Ideally initial experience with ROS
Interest in grasping textile materials

This topic is suitable for a bachelor’s, project or master’s thesis and can also be combined with further topics for an M-APR.

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

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

Grasping Unknown Components for Robotic Assembly

Motivation

Topic Area

Description

Requirements

Supervision

Handling of Films and Paper Interlayers

Motivation

Topic Area

Description

Requirements

Supervision