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Projekt M-MACH-106381
Dear students,
Registration for the project will be open from 12:00 a.m. on September 29 to 11:59 p.m. on October 12. Please note that we cannot accept late registrations. You can register using the SignMeUp tool at https://plus.campus.kit.edu/signmeup/procedures/5470
Below you will find an overview of the individual topics within each area.
If you have any questions, please do not hesitate to contact us. You will find the contact details at the bottom of the page.
Methodically
Control of an in-situ miniature loading device via LabVIEW
A LabVIEW-based control routine will be developed for an existing miniature loading device designed for in-situ X-ray diffraction analyses of metallic samples under mechanical stress. This will allow automated, complex loading cycles under load and strain control. The control of the loading tests and data acquisition will be carried out via an attractive and intuitive user interface (GUI). Ultimately, the entire device will be put into operation, and initial in-situ diffraction analyses under load will be performed on laboratory X-ray machines. The project also offers the opportunity to propose and implement design improvements to the existing test setup.
Experimental
Manufacturing and Characterization of precipitation strengthened Al alloys
Precipitation hardening is a key mechanism for strengthening aluminum alloys. Targeted heat treatments can produce coherent or incoherent precipitates of various sizes. These precipitates effectively impede dislocation movement, thus improving strength. The aim is to optimize the microstructure to develop high-strength, formable alloys for industrial applications, such as in the aerospace industry. In this project, students will focus intensively on manufacturing and characterizing the mechanical properties of an aluminum alloy with different heat treatment states.
3D-Printed Meta- Sandwich Structures for Lightweight Drone Frames
Lightweight sandwich structures are widely used in high-performance engineering applications. They are comprised of two thin face sheets at the top and bottom surface separated by a lightweight cellular core – commonly a foam with a random spatial layout. Advances in additive manufacturing today enable cellular structures which are patterned from rationally architected 3D building blocks– so-called Metamaterials -with superior weight efficiency. You will develop a metamaterial-based sandwich architecture for a lightweight drone frame prototype. Your team will design architecture layouts using analytical and numerical mechanical models, 3D-print sandwich plate test structures, and characterize those experimentally under compression and bending.
Oxidation Behavior of Cr-Mo-Si alloys
Climate change and the resulting energy transition present significant challenges to science and industry. They must make existing systems, which are based on the combustion of fossil fuels and cannot be replaced by fully electric systems in the foreseeable future, more efficient. Novel high-melting refractory metal alloys offer promising properties for increasing combustion temperatures in gas turbines and for preventing efficiency losses due to cooling engine components. However, these alloys often have insufficient oxidation resistance at very high temperatures. Therefore, this project aims to investigate the isothermal and cyclic oxidation properties of a new alloy in the Cr-Mo-Si system.
Hydrogen effects in metal films
Hydrogen is a central vector in the energy transition with many materials science aspects. For example, the renewable energy generated from solar and wind energy can be chemically stored in metals using hydrogen. When needed, the hydrogen can be utilized in fuel cells or through direct combustion. In contact with construction materials, hydrogen can lead to hydrogen embrittlement and change the mechanical properties of the metal. In this project, you will develop the fundamentals of the interaction of hydrogen with metals and investigate which microstructural changes hydrogen can induce in metal. You will use a film deposition method (sputter deposition), optimize the design of a hydrogen loading cell, and develop data acquisition software to measure hydrogen effects
Realization and programming of a table control and analysis for a scanning-Raman-system
At the institute, a friction test bench with a Raman spectrometer enables pointwise analysis of sample composition. The sample is excited with a green laser, and the frequency shift of scattered light is measured. To create a chemical map, the sample is scanned, and individual measurements are combined into an image. The project aims to develop a table control system that moves the sample in x- and y-directions with a defined pixel number. A Raman measurement is performed at each point, and results are mapped. Tasks include component programming, test bench experiments, and evaluation programming.
Numerical / Theoretical
Design, optimization and fabrication (3D printing) of a lightweight gearbox
A gearbox housing for a single-stage gear unit is to be designed and manufactured using an FFF 3D printer in PLA. The goal is to transmit a specified load spectrum (forces and torque) within a given installation space while using as little material as possible. The design should be carried out using the Finite Element Method (FEM), taking into account the anisotropy caused by the manufacturing process. For this purpose, a Python program must be written that uses the G-code generated by the slicer to create local material orientations as input for the FE analyses.
Simulation of fiber-reinforced lightweight structures considering variable material and manufacturing effects
The development of robust lightweight structures requires reliable simulation models and fast optimization methods for fiber composites. In this project, linear elastic FEM simulations based on open-source geometries (ABC data set) are to be created and run with various force or displacement boundary conditions. In addition, fiber and matrix stiffnesses and fiber orientations are to be varied to simulate different material compositions. The resulting stress and deformation fields can then be used for the analysis of mechanical load cases and for the generation of data sets to train AI models, thus supporting process and component development in lightweight construction.
Numerical simulation of coupled temperature and crystallization evolution in thermoplastics
The manufacturing of thermoplastics involves heat transfer, which strongly affects crystallization. Since crystallization is exothermic, the released heat must be included in a simulation model. One approach is to model the heat-source term in the heat equation as dependent on crystallization and cooling rates. The Nakamura model can describe the time evolution of the degree of crystallinity. This project focuses on implementing a Python numerical solver that accounts for the coupled evolution of temperature and crystallinity. The solver will operate on a two-dimensional domain. Sensitivity studies will be performed based on this solver.
Simulation of discontinuous fiber-reinforced plastics along the virtual process chain
In virtual product development of parts made from compression-molded discontinuous fiber-reinforced polymers, mold filling and warpage simulations are crucial. These process steps determine the fiber distribution in the part and cause process-related deformations, which greatly affect component performance and dimensional accuracy. As part of the semester project, simulation methods will first be used to predict fiber orientation and temperature distributions resulting from flow. These field variables then serve as inputs for the warpage simulation. Finally, process parameters such as tool temperature or initial material placement in the tool will be varied in a parameter study and analyzed for their significance.
Numerical simulation of flow and heat transport in geothermal fractures
Heat transport and transfer for fluid flow through fractures geothermal reservoirs is important for the efficiency assessment and optimisation of geothermal energy extraction systems. The fracture geometry, flow and thermal conditions influence how effectively heat is transferred from the rock to the fluid, thereby affecting the system efficiency. Numerical simulations help to understand and predict these transport processes. Simulation studies for different fracture geometries and with varying parameters, e.g. different flowrates, are used for this purpose. The task involves generating realistic fracture geometries, conducting simulation studies with flow and heat transfer under different conditions, and subsequent evaluation of the results.
Methodically
Small-Scale Material Handling - Exploration of Scaling Laws
Conveyor belts and robots are usually known on a meter scale – but what happens when we reduce the technology to a few centimeters? In this project, you will experimentally investigate various conveyor belts in the laboratory and explore the question of whether the known design methods also apply on a small scale. The goal is to develop your own scaling laws that describe the transfer from large to small. This will give you exciting insights into a technology that is becoming increasingly important for industries such as pharmaceuticals, chemicals, and electronics.
Digital fingerprint: Setup and computer vision application for component identification
Modern image processing methods allow components to be identified using camera images of surfaces, eliminating the need for barcodes. Your goal in this project is to design a station for capturing images and to develop a computer vision application for registering and recognizing components. To this end, you will work in your team on the design of the station and the selection of hardware components (e.g., camera, lighting) as well as in the areas of data science, machine learning, and software development. The end result will be a physical demonstrator, a training data set, a machine learning pipeline, and a software prototype.
GenCAD: Automatic Design of Suction Grippers for Complex Components
The design of component-specific grippers in automation and robotics involves high manual effort and is both time-consuming and costly. The goal of this project is therefore the development of algorithms for the automated generation and optimization of suction gripper designs for handling complex components. To achieve this, your team is working on a software prototype that automatically determines grasp points on the component, parametrically defines the gripper body, implements it through CAD operations, and subsequently evaluates it in simulation. Along the way, you will gain experience with Python libraries for code-based generation of parametric CAD models, black-box optimization of grasp points, and physical simulation.
Experimental
Multimodal Perception for Urban Road Users
This project will develop a multimodal perception system for pedestrians, cyclists, vehicles, and trams using roof-mounted sensors (3 cameras + 6 LiDARs). The work includes four main tasks: (1) static camera perception, (2) static LiDAR perception, (3) multi-sensor object tracking combining camera and LiDAR features, and (4) generation of smooth trajectories and fixed-size 3D bounding boxes for tracked objects. If time allows, results will be extended to train an end-to-end model. The setup is fully calibrated, sufficient data is already available, and additional recordings can be collected. The project suits 3–4 students working collaboratively.
Applied AI in Robotics: Four-Legged Walking Robots Under Load
You will work in a team to teach a dog-like robot (Unitree Go2) to walk robustly using machine learning. In the NVIDIA Isaac Lab simulation environment, you will train the locomotion using carefully selected reward terms that optimise stability and speed despite additional loads on the back of the robot. You will then transfer the models to the real robot to test its behaviour with known and unknown loads. Then you need to evaluate the quality of the Sim2Real transfer using a custom metric. This allows you to acquire practical skills at the intersection of robotics, AI and experimental validation.
Actuation in a strong magnetic field
Robotics inside strong magnetic fields is very challenging, because many usual materials and mechanisms do not work well, and space is limited. In this project, you will consider the constraints, and invent a manufacturable technology that allows kinematic elements and precise movements, to achieve modular robotic building blocks.
Industry 5.0 ready? Using LLMs for automating intralogistics systems.
Can ChatGPT do more than just chat? Find out in this project! Using a small-scale demonstrator consisting of conveyor belts, mobile robots, and robotic arms, you will develop solutions that understand and implement logistics tasks from natural language. In the process, you will learn the basics of Industry 5.0 and LLM agents and implement your ideas directly on the hardware—based on an existing code base. This will allow you to bring modern AI technologies into the factory of the future in a practical way.
Affordable sub µm Motion Control
In next generation 3D printing based on filament feedstocks, the filament is generated just-in-time, and emerges at a high speed from the printhead. Its diameter is below 1 µm, so that the relative positioning of printhead to substrate has to be precisely controlled, and executed at sufficiently high speed. In this project you will conceive of a suitable actuation principle, and control electronics, to move a substrate below a precision printhead and build a 'benchy' at the microscale.
Development and extension of a teleoperation interface for a robot arm with haptic feedback
As part of the project, students will reconstruct the existing teleoperation system GELLO and adapt it for our UR10 robot. They will extend it with haptic feedback using a self-developed tactile sensor: a barometer module encapsulated in silicone to measure pressure changes on contact. These signals drive a vibration motor, giving the operator direct tactile feedback. Tasks include mechanical setup, design and 3D printing of housings, integration of electronics and sensors, calibration, signal processing, and experimental testing. Interfaces to robot control will be created, and system responses to different types of contact will be investigated.
Microactuator applications based on smart materials
Smart materials are characterized by their multifunctional properties, in particular their sensor and actuator functions. These include shape memory alloys, which undergo large, abrupt changes in their physical properties due to a phase transformation. The project aims to manufacture novel microactuators based on smart materials and characterize them thermally, electrically, and mechanically. Examples of microactuator applications include thermomagnetic microactuators, which convert thermal energy into kinetic energy to generate electricity, and self-folding microactuators made of shape memory alloys based on the art of origami. This work builds on existing expertise in microfabrication technology and measurement and control engineering. Translated with DeepL.com (free version)
Additive manufacturing of a changing station for vacuum suction pads
The project aims to develop and prototype a change station for vacuum grippers based on a Schmalz end piece. The goal is a reliable, airtight mechanism that enables the use of different gripper attachments. Switching can be performed partly by the robot itself or via an integrated mechatronic system in the station. Tasks include designing and 3D printing mounts, interfaces, sealing concepts, and various gripper sizes. Vacuum channels, locks, and guides must also be designed. The solution will be tested for tightness, repeatability, and changeover time. Work packages: CAD design, calculations, prototyping, test protocols, documentation, and final presentation.
Robotics in Action: Programming, Control, Automation
In this module, you will work hands-on with an industrial robot in a team and learn to apply modern robotics using open-source software. You will begin by setting up a development environment (ROS2) and controlling a UR10e cobot with MoveIt, then gradually build your own intelligent robot application. Changes to the robot cell will be transferred to a virtual URDF model, enabling collision-free motion planning and the implementation of state machines for more advanced tasks. Finally, you will test and evaluate pick-and-place functions in a commissioning scenario supported by a Realsense camera, gaining expertise from robotics basics to intelligent automation.
Design of a clamping system for automatic measurement of gears
Image-based measurement technology is becoming increasingly important in modern manufacturing, as it enables fast, contactless, and precise detection of workpieces during the manufacturing process. Especially in the case of gears, accurate measurement is crucial for determining process-relevant parameters. The aim of the project is to develop a system that enables interaction between robots and cameras. The robot's gripper is to be adapted so that gears can be securely fixed and positioned using a simple robot path. These are then to be measured using image processing algorithms. Students will deepen their knowledge of mechanical design and acquire skills in robot control, AI-supported image processing, and industrial communication.
Active and Continual Learning for Autonomous Driving
Join the Frontier of AI for Autonomous Driving! Are you ready to push boundaries in active and continual machine learning for real-world AI? In this project, you’ll develop cutting-edge pipelines where models learn on the fly from user feedback—adapting to new cities, labeling styles, and missions. Tackle challenges like catastrophic forgetting, design efficient training and annotation loops, and integrate your work directly into AI-enhanced labeling software. We provide GPUs, datasets, and mentoring — you bring curiosity, coding skills, and the drive to experiment beyond the script. This is research-level engineering: tough, exciting, and perfect for ambitious students.
Numerical / Theoretical
Model creation and simulation with a hydraulics library for Modelica
As part of this project, an existing Modelica hydraulics library is to be extended. The goal is to model additional hydraulic components as well as example models of simple hydraulic systems and to represent them graphically in accordance with DIN ISO 1219. In addition, a user manual or illustrative tutorial videos can be created to demonstrate the library/example models. The project combines modeling, simulation, technical documentation, and multimedia preparation in an engaging way, making it ideal for students interested in simulation and hydraulics.
Development of a ROS based Tool to calculate Vehicle Speed using LiDAR-Data
The use of LiDAR sensors in highly automated driving is particularly relevant: they enable both object detection and motion estimation (odometry). The latter includes determining speed and acceleration, where LiDAR and IMU data are often combined. Since IMU signals are unreliable in forest environments, this project will investigate how the velocity of forestry machines (forwarders, harvesters) can be estimated solely from LiDAR point clouds. Based on recorded ROS bags, methods from the literature will be analyzed, visualized, and compared. The selection and number of algorithms will be defined in consultation with the supervisor and depend on group size.
Methodically
Conception and Design of a drivetrain system
A wide variety of drive systems differ depending on the application. City cars, excavators, sailboats, skidoos, harvesters, etc. are characterized by different requirements. As part of the project, a special application is defined for which a suitable energy conversion concept is to be selected and designed.
Development of a dashboard with Python for visualisation of measurement data
Knowledge and improvement of energy conversion processes is crucial for the research and development of modern drive systems (passenger cars, commercial vehicles, off-highway vehicles, marine, etc.). Test benches are required to analyze these energy conversion processes.
One challenge here is the analysis of a very large amount of measurement data (temperature, pressure, flow velocities, speeds, concentrations, density, voltage, current, etc.), which also occurs under a wide range of operating conditions (speed, load, temperature, etc.) and varies accordingly. Rapid analysis of the large amount of data generated is therefore of great importance.
As part of this project, a dashboard is to be developed that graphically processes the test bench data and enables fast and intuitive analysis.
Experimental
Elastocaloric Cooling with Polymer Films: Next-Generation Low-Cost Cooling
Cooling is one of the largest global energy demands, and new technologies are urgently needed. Elastocaloric cooling is considered by the EU as the most promising next-generation cooling technology, since it uses solid materials that heat up and cool down under mechanical stress, avoiding harmful refrigerants. Polymer films are especially attractive because they combine excellent heat transfer with low cost. In this project, you will investigate their thermal and mechanical behavior, design and build a small-scale cooling demonstrator, and evaluate performance using IMT’s advanced infrastructure. The work is interdisciplinary and includes international collaboration with INSA France.