Department of Mechanical and Process EngineeringAcronym | D-MAVT | Homepage | http://www.mavt.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Mechanical and Process Engineering | Child organizations | |
Open OpportunitiesIn this project, we are going to develop a vision-based reinforcement learning policy for drone navigation in dynamic environments. The policy should adapt to two potentially conflicting navigation objectives: maximizing the visibility of a visual object as a perceptual constraint and obstacle avoidance to ensure safe flight. - Engineering and Technology
- Master Thesis
| Recent research has demonstrated significant success in integrating foundational models with robotic systems. In this project, we aim to investigate how these foundational models can enhance the vision-based navigation of UAVs. The drone will utilize learned semantic relationships from extensive world-scale data to actively explore and navigate through unfamiliar environments. While previous research primarily focused on ground-based robots, our project seeks to explore the potential of integrating foundational models with aerial robots to enhance agility and flexibility. - Engineering and Technology
- Master Thesis, Semester Project
| Drying (e.g. Pasta drying) is the most energy intensive process step, sometimes taking up more than 50% of the total energy consumption of a plant. Superheated steam drying could present an energy efficient alternative to classical hot-air drying systems used today. This new technology could have a massive impact on the carbon-footprint and sustainability of food-drying; making it a highly future-oriented and potentially impactful innovation. - Interdisciplinary Engineering, Manufacturing Engineering, Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| Cutting-edge tools play a pivotal role in manufacturing processes, enduring wear and damage while consistently producing series of components. Maintaining an optimal cutting-edge geometry is crucial to uphold the quality of finished products over time. Additionally, sustaining the micro-geometry of the cutting edge is key to enhancing the lifespan of the tool and ensuring top-notch cutting performance. Profin addresses this challenge with Flakkotting, a novel surface finishing process designed explicitly to create and preserve the required micro-geometry.
The aim of this thesis is to develop the understanding of Flakkotting process and develop prediction model for process parameters for a given micro-geometry. The dynamics of flakkotting tools on Tungsten Carbide drills and cutting-edge inserts will be studied with varying parameters using high-speed imaging and microscopic analysis. Using the parameter data and evaluated workpieces, machine learning (ML) models will be developed for prediction of micro-geometry features and optimization of process based on the required micro-geometry. - Computer Vision, Manufacturing Engineering, Mechanical Engineering, Statistics
- Bachelor Thesis, Master Thesis
| Direct Air Capture (DAC) of carbon dioxide (CO2) is a promising technology to combat climate change by removing CO2 directly from the atmosphere. One approach to DAC involves the accelerated weathering of calcium hydroxide (Ca(OH)2), a process where CO2 exothermically reacts with Ca(OH)2 to form calcium carbonate (CaCO3) and water. A two-step regeneration allows for a cyclic process. In the first regeneration step, CaCO3 is sent into a high-temperature reactor. Inside this reactor, the CaCO3 decomposes into calcium oxide (CaO) and CO2 at temperatures near 900 ÂșC at atmospheric conditions. The calcium oxide is then hydrated in the second stage to form Ca(OH)2. The hydration reaction is exothermic and presents a suitable opportunity for heat recovery. The resulting Ca(OH)2 is newly used as the sorbent material in the capture step.
Understanding the behavior and sensitivity of this process to key operating conditions is crucial for optimizing its performance and energy efficiency. Moreover, the influence of water on the porous calcium oxide (CaO) sorbent material for CO2 adsorption represents a crucial aspect of process optimization.
- Process Control and Simulation
- ETH Zurich (ETHZ), Master Thesis
| In this project, you will investigate the use of event-based cameras for vision-based landing on celestial bodies such as Mars or the Moon. - Engineering and Technology
- Master Thesis, Semester Project
| The Swiss watch industry focuses on perfectioning their capabilities since its beginnings. The use of printable, protective elements during surface finishing processes would allow for a new level of resolution and complexity. Nevertheless, currently used materials are not printable due to their high viscosity and are often hard to remove. We therefore are developing a printable polymeric coating that allows for traceless removal with water. - Chemical Engineering, Colloid and Surface Chemistry, Industrial Chemistry, Macromolecular Chemistry, Manufacturing Engineering, Mechanical Engineering, Polymers
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| Despite the growing amount of work on applying causal discovery method with expert knowledge to areas of interest, few of them inspect the uncertainty of expert knowledge (what if the expert goes wrong?). This is highly important since that in scientific fields, causal discovery with expert knowledge should be cautious and an approach taking expert uncertainty into account will be more robust to potential bias induced by individuals. Therefore, we aim to develop an iterative causal discovery method with experts in the loop to enable continual interaction and calibration between experts and data.
Based on the qualifications of the candidates, we can arrange a subsidy/allowance for covering traveling or living costs. - Expert Systems, Health Information Systems (incl. Surveillance), Statistics
- Internship, Master Thesis, Semester Project
| This project focuses on developing an explainable Artificial Intelligence (xAI) framework based on graphical modeling (GM), to enhance the capacity and capability of medical AI. Collaborating with the Swiss Paraplegic Centre (SPZ) for validation, our goal is to improve the long-term prognosis of spinal cord injury (SCI) individuals. Through medical records and a multimodal sensory monitoring system, we aim to create digital twins capable of integrating diverse data sources, guiding medical treatment, and addressing common secondary health conditions in the SCI population. The envisioned GM-based digital twin (GMDT) will represent hierarchical relations across demographic features, functional abilities, daily activities, and health conditions for SCI individuals, allowing for downstream tasks such as prediction, causal inference, and counterfactual reasoning. The assimilation and evolution between the physical and digital twins will be implemented under the GM framework, promising advancements in personalized healthcare strategies and improved outcomes for SCI people. Please refer to the attached document for more details about the task description. Based on the candidate's qualifications, funding/allowance can be provided. - Biomedical Engineering, Digital Systems, Knowledge Representation and Machine Learning, Pattern Recognition, Simulation and Modelling
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The process of evaluating sleep examinations and diagnosing sleep disorders through polysomnographies (PSGs) is labor-intensive as it requires manual analysis from sleep technicians and doctors. In collaboration with Clinic Barmelweid, a leading sleep and rehabilitation clinic in northwestern Switzerland, we plan to automate this process using machine learning models. Clinic Barmelweid conducts approximately 400-450 PSGs annually and has access to a dataset of more than 5,000 recordings. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Medical and Health Sciences
- Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
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