Department of Mechanical and Process Engineering

Open Opportunities

Utilizing human body for ambient electromagnetic energy harvesting ETH Zurich Biomedical and Mobile Health Technology Lab The goal of the project is to develop wearable devices, for use in environmental electromagnetic energy recovery based on human body application. Biomedical Engineering, Electrical and Electronic Engineering, Materials Engineering Bachelor Thesis, Master Thesis, Semester Project

Mechanophores for advanced wearable strain and pressure sensors ETH Zurich Biomedical and Mobile Health Technology Lab The goal of the project is to synthesize and characterize a number of small molecules capable of acting as mechanophore addition to various polymers. These polymers would then be used as wearable strain or pressure sensors. Chemical Engineering, Chemistry, Composite Materials Master Thesis

Point-of-Care Sensor for Urinary Iodine ETH Zurich Biomedical and Mobile Health Technology Lab The goal of the project is to develop a cheap and disposable sensor capable of determination of iodine levels in human urine for early diagnostic purposes. Chemistry, Engineering and Technology, Medical and Health Sciences Master Thesis

Cyclic Siloxanes - Test Setup Development and Material Screening ETH Zurich Human-centered Sensing Laboratory Cyclic siloxanes pose a critical risk to cleanroom manufacturing quality; their filtering is thus of utmost importance. Materials Engineering, Mechanical Engineering ETH Zurich (ETHZ), Master Thesis

Metal oxide-based textile logic electronics ETH Zurich Biomedical and Mobile Health Technology Lab The goal of the project is to develop metal oxide-based logic electronics, for use in rectification and/or memristor application. Biomedical Engineering, Electrical and Electronic Engineering, Materials Engineering Bachelor Thesis, Master Thesis, Semester Project

Volumetric Imaging of Natural Snowfall Formations in the Field ETH Zurich Group Coletti The interaction between natural snowfalls and atmospheric wind conditions can lead to complex snow clustering dynamics mediated by turbulence. For example, the formations of columnar structures and kinematic waves such as those present in particle-laden flows. How do such complex systems composed of millions of snowflakes lead to structure in the presence of a large variety of atmospheric turbulence conditions? Which kind of structures form depending on the snow mass loading, the type of frozen hydrometeor, and the atmospheric turbulence intensity levels? Building on a previous project that performed planar imaging, this project will focus on performing volumetric field imaging. Measurements will be performed at a professional field site in Davos where a holography setup will collocate snowflake characterization. To process the imaging data the student will join forces at the DLR in Göttingen and track snowflakes using state-of-the-art ‘Shake-the-Box’ Lagrangian particle tracking methodology. Aerospace Engineering, Earth Sciences, Environmental Engineering, Mathematical Sciences, Mechanical Engineering, Physics ETH Zurich (ETHZ), Master Thesis

Agile Flight of Flexible Drones in Confined Spaces University of Zurich Robotics and Perception The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints. Control Engineering, Flight Control Systems, Intelligent Robotics, Systems Theory and Control Master Thesis, Semester Project

Vision-Based World Models for Real-Time Robot Control University of Zurich Robotics and Perception This project aims to use vision-based world models as a basis for model-based reinforcement learning, aiming to achieve a generalizable approach for drone navigation. Computer Vision, Intelligent Robotics, Simulation and Modelling Master Thesis, Semester Project

Vision-Based Reinforcement Learning in the Real World University of Zurich Robotics and Perception We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning. Computer Vision, Flight Control Systems, Intelligent Robotics Master Thesis, Semester Project

Efficient Sampling-based GP-MPC for autonomous robots ETH Zurich Research Zeilinger Most control methods operate under the assumption of a known model. However, in practice, knowing the exact dynamics model a priori is unrealistic. A common approach is to model the unknown dynamics using Gaussian Processes (GPs) which can characterize uncertainty and formulate a Model Predictive Control (MPC) type problem. However, it is difficult to exactly utilize this uncertainty characterization in predictive control. In a recent approach [1], we proposed a sampling-based robust GP-MPC formulation for accurate uncertainty propagation by sampling continuous functions. In contrast, in the proposed project, you will implement an approximation method for sampling continuous functions using a finite number of basis functions [2] and solve the MPC problem jointly with the sampled dynamics. You will analyze the trade-offs between performance, approximation accuracy, and computational cost for this method. Engineering and Technology Master Thesis, Semester Project