Student Projects
Student Projects by Associated Institutes
Low-Dose CT Phantom for Neonates & Children – Materials, Manufacturing & Clinical Validation
Three-dimensional medical imaging techniques such as Computed Tomography (CT) and MRI are indispensable in modern clinical workflows. CT utilizes X-rays acquired from multiple angles to reconstruct detailed volumetric patient anatomy data. Due to the harmful effects of ionizing radiation, especially in vulnerable populations such as infants, it is critical to minimize radiation exposure while maintaining diagnostic image quality. Optimizing CT parameters requires systematic studies, yet direct experimentation on infants is ethically and medically unacceptable. This project aims to develop a novel infant head phantom that accurately replicates the radiological properties of an infant’s head. The phantom will serve as a testbed for CT imaging studies, enabling the optimization of scan parameters that balance minimal radiation exposure with high-quality image acquisition tailored for pediatric neuroimaging.
Keywords
pediatric CT imaging, child radiation safety, low-dose CT, medical imaging phantom, 3D-printed phantom, biomedical engineering thesis, materials for radiology, imaging dose reduction, ETH Zurich research, clinical radiology innovation
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-04-30 , Earliest start: 2025-05-01
Applications limited to ETH Zurich
Organization Multiscale Robotics Lab
Hosts Landers Fabian
Topics Engineering and Technology
Feedback Optimization of Acoustic Patterning in Real Time for Bioprinter
Our project aims to enhance the ultrasound-assisted bioprinting process using real-time feedback and image processing. We have developed a transparent nozzle equipped with multiple cameras for real-time monitoring. The next steps involve integrating advanced image processing techniques, such as template matching, and implementing a feedback system to optimize the printing process. The system will be fully automated, featuring a function generator for wave creation and cooling elements. By analyzing the printing process and acoustic cell patterning with computer vision and leveraging real-time sensor feedback, we aim to dynamically optimize parameters such as frequency and amplitude for accurate and consistent pattern formation, crucial for bio applications.
Keywords
Machine learning, control and automation, 3D Printing, Ultrasound
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Bachelor Thesis , Master Thesis
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Published since: 2025-04-29 , Earliest start: 2025-02-01 , Latest end: 2025-09-30
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Medany Mahmoud
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
BEV meets Semantic traversability
Enable Birds-Eye-View perception on autonomous mobile robots for human-like navigation.
Keywords
Semantic Traversability, Birds-Eye-View, Localization, SLAM, Object Detection
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-04-29 , Earliest start: 2025-01-15 , Latest end: 2025-10-31
Organization Robotic Systems Lab
Hosts Gawel Abel
Topics Information, Computing and Communication Sciences , Engineering and Technology
Scene graphs for robot navigation and reasoning
Elevate semantic scene graphs to a new level and perform semantically-guided navigation and interaction with real robots at The AI Institute.
Keywords
Scene graphs, SLAM, Navigation, Spacial Reasoning, 3D reconstruction, Semantics
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-04-29 , Earliest start: 2025-01-15 , Latest end: 2025-10-31
Organization Robotic Systems Lab
Hosts Gawel Abel
Topics Information, Computing and Communication Sciences , Engineering and Technology
Modelling and Optimizing the Power Budget of a Bridge-Mounted Camera System for River Waste Monitoring
In this thesis, you will contribute to the Autonomous River Cleanup (ARC) by helping develop SARA, a bridge-mounted, camera-based system for monitoring river waste. Your focus will be on modeling the system’s power dynamics to determine the ideal battery and solar panel size, and balancing runtime throughout the day with overall the system size and weight. If time allows, you will also validate your findings with tests on the real hardware.
Keywords
system modelling, power electronics, simulations
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Semester Project , Bachelor Thesis
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Published since: 2025-04-27 , Earliest start: 2025-05-05 , Latest end: 2025-09-30
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Elbir Emre
Topics Engineering and Technology
Domain Adaptation Techniques for Vision Algorithms on a Smartphone for River Waste Monitoring
In this thesis, you will work on SARA, a bridge-mounted, smartphone-based system for detecting and monitoring river waste. The focus will be on selecting lightweight detection and classification models suitable for smartphones and exploring domain adaptation techniques to improve performance across different locations with minimal retraining. Your work will build on previous research at ARC and current literature to develop solutions that balance model robustness and computational efficiency.
Keywords
machine learning, computer vision, domain adaptation techniques
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Semester Project
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Published since: 2025-04-27 , Earliest start: 2025-05-05 , Latest end: 2025-09-30
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Elbir Emre
Topics Engineering and Technology
Optimal Robot Configuration for Autonomous Waste Sorting in Confined Spaces
In this thesis, you will contribute to the Autonomous River Cleanup (ARC) by helping improve MARC, our robotic platform for autonomous waste sorting. Your work will focus on optimizing the robot arm configuration by simulating different base locations and degrees of freedom to achieve faster and more efficient pick-and-place movements in a confined space. You will build on our existing simulation environment to model and evaluate various setups.
Keywords
modelling and simulations, robotics, robot dynamics
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Semester Project
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Published since: 2025-04-27 , Earliest start: 2025-05-05 , Latest end: 2025-09-30
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Elbir Emre
Topics Engineering and Technology
Thermal Protection of a Bridge-Mounted Camera System for River Waste Monitoring
The Autonomous River Cleanup (ARC) is developing SARA, the next iteration of a bridge-mounted, camera-based system to detect and measure riverine waste. Smartphones offer a compact, affordable, and powerful core for year-round monitoring but are vulnerable to shutdowns from extreme heat in summer and cold in winter. This thesis focuses on assessing these thermal challenges and designing protective solutions to ensure reliable, continuous operation.
Keywords
thermodynamics, heat transfer, testing
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Semester Project , Bachelor Thesis
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Published since: 2025-04-27 , Earliest start: 2025-05-05 , Latest end: 2025-09-30
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Elbir Emre
Topics Engineering and Technology
Utilizing human body for ambient electromagnetic energy harvesting
The goal of the project is to develop wearable devices, for use in environmental electromagnetic energy recovery based on human body application.
Keywords
Flexible electronics, electromagnetic energy harvesting
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-04-23 , Earliest start: 2025-05-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Li Yuanlong
Topics Engineering and Technology
Mechanophores for advanced wearable strain and pressure sensors
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.
Keywords
mechanophore, polymer, wearable, sensor, color, strain, pressure
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Master Thesis
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Published since: 2025-04-22 , Earliest start: 2024-09-01 , Latest end: 2025-09-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Engineering and Technology , Chemistry
Point-of-Care Sensor for Urinary Iodine
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.
Keywords
electrochemistry, iodine, nutrition, health, point of care
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Master Thesis
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Published since: 2025-04-22 , Earliest start: 2025-01-01 , Latest end: 2025-10-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Metal oxide-based textile logic electronics
The goal of the project is to develop metal oxide-based logic electronics, for use in rectification and/or memristor application.
Keywords
Metal oxide, smart textile, wearable electronics, logic electronics, electrochemistry
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-04-21 , Earliest start: 2025-05-31 , Latest end: 2025-11-30
Organization Biomedical and Mobile Health Technology Lab
Hosts Li Yuanlong
Topics Engineering and Technology
Agile Flight of Flexible Drones in Confined Spaces
The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints.
Keywords
Robotics, Autonomous Systems, Model Predictive Control, Quadcopter, Drone Racing, Approximate Dynamic Programming, Model-Based Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-04-17 , Earliest start: 2025-06-01 , Latest end: 2026-03-01
Organization Robotics and Perception
Hosts Reiter Rudolf
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Vision-Based World Models for Real-Time Robot Control
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.
Keywords
Robotics, Autonomous Systems, Computer Vision, Foundation Models, Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-04-17 , Earliest start: 2025-05-01 , Latest end: 2026-02-28
Organization Robotics and Perception
Hosts Reiter Rudolf
Topics Information, Computing and Communication Sciences
Vision-Based Reinforcement Learning in the Real World
We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning.
Keywords
Robotics, Autonomous Systems, Computer Vision, Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-04-17 , Earliest start: 2025-05-01 , Latest end: 2026-02-01
Organization Robotics and Perception
Hosts Reiter Rudolf
Topics Information, Computing and Communication Sciences , Engineering and Technology
Meta-model-based-RL for adaptive flight control
This research project aims to develop and evaluate a meta model-based reinforcement learning (RL) framework for addressing variable dynamics in flight control.
Keywords
Model-based Reinforcement Learning, Meta Learning, Drones, Robotics
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Master Thesis
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Published since: 2025-04-10 , Earliest start: 2025-05-01 , Latest end: 2026-04-30
Organization Robotics and Perception
Hosts Geles Ismail
Topics Information, Computing and Communication Sciences , Engineering and Technology
Language-guided Drone Control
Explore the use of large vision language models to control a drone.
Keywords
Human-drone interaction, large language models (LLMs), Robotics
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Semester Project , Master Thesis
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Published since: 2025-04-10 , Earliest start: 2025-05-01 , Latest end: 2026-02-28
Organization Robotics and Perception
Hosts Geles Ismail
Topics Information, Computing and Communication Sciences , Engineering and Technology
Hardware Design Internship in Brain Imaging
Join us in revolutionizing brain imaging technologies and make it accessible for everyday use. Functional near-infrared spectroscopy (fNIRS) is an emerging technology that enables cost-effective and precise brain measurements, helping to improve neurotherapies and brain health.
Keywords
3D-printing, injection molding, design, brain imaging, neuro, wearables, health, startup
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Internship
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Published since: 2025-04-09 , Earliest start: 2025-04-10 , Latest end: 2025-06-26
Organization Rehabilitation Engineering Lab
Hosts Wyser Dominik
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Smart Microcapsules for Biomedical Advances
This Master's thesis/semester project focuses on the microfluidic fabrication of microcapsules with multi-environmental responsiveness. The aim is to develop microcapsule-based microrobots capable of adapting to various environmental cues. We envision that these microrobots will be used for complex tasks in biomedical applications.
Keywords
Microfluidics, Microcapsules, Microrobotics, Responsive Polymers, Biomedical Engineering
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Semester Project , Internship , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-04-08 , Earliest start: 2025-07-01
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Low-Voltage Soft Actuators for Developing Untethered Robotic Systems
We are building the next generation of HALVE (Hydraulically Amplified Low-Voltage Electrostatic) actuators which are flexible, pouch-based electrostatic actuators that operate at voltages 5–10× lower than traditional soft electrostatic systems. You will help us explore novel actuator geometries, ultra-thin functional layers, and new fabrication techniques to unlock scalable, energy-efficient soft robotic systems.
Keywords
soft robotics, low-voltage actuation, dielectric elastomers, electrostatic actuators, fabrication, PVDF-TrFE-CTFE, vapor deposition, CNC sealing, mechatronics, materials science
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-04-07 , Earliest start: 2025-04-14 , Latest end: 2026-01-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa
Organization Soft Robotics Lab
Hosts Albayrak Deniz , Hinchet Ronan
Topics Engineering and Technology
Combined Muscle and Nerve Tissue Engineering
Engineered muscle tissues have applications in regenerative medicine, drug testing, and understanding motion. A key challenge is restoring neuromuscular communication, especially in treating volumetric muscle loss (VML). This project aims to create functional neuromuscular constructs with biomimetic innervation. Scaffolds will be made using electrospun fibers, conductive materials, and drug-loaded graphene. Muscle and nerve cells derived from iPSCs will be seeded into these scaffolds. Constructs will be tested for motion, drug response, and integration in bio-hybrid robotic systems. The platform will advance muscle-nerve regeneration, drug testing, and bio-hybrid robotics.
Keywords
Tissue engineering, innervation, neural tissue, nerve, muscle tissue, scaffold, iPSCs, muscle cells, bioprinting, biofabrication, biohybrid robotics, soft robotics, 3D printing, biomaterials, electrical stimulation, actuation.
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Semester Project , Master Thesis
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Published since: 2025-04-06 , Earliest start: 2025-04-06 , Latest end: 2025-09-30
Organization Soft Robotics Lab
Hosts Filippi Miriam
Topics Medical and Health Sciences , Engineering and Technology , Biology
Continual Learning and Domain Adaptation Techniques for a Camera-Based Waste Monitoring System on an Ocean Cleanup Vessel
This thesis, part of the Autonomous River Cleanup (ARC) initiative in collaboration with The SeaCleaners, explores adaptive computer vision methods for automated quantification of oceanic plastic waste on the Mobula 10 vessel. The work focuses on applying continual learning and domain adaptation techniques to improve a baseline detection model’s robustness to changing waste types and environments. The system will be evaluated in real-world conditions to assess its performance and guide future research in environmental monitoring.
Keywords
computer vision, continual learning, field testing, unsupervised domain adaptation, plastic pollution
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Master Thesis
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Published since: 2025-03-26 , Earliest start: 2025-05-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Stolle Jonas , Elbir Emre
Topics Engineering and Technology
Master Thesis / Project - SENSEI: Sensor Teaching in Multi-Activity classification from Video and Wearables for Wheelchair Users
In this project, we focus on continuous and quantitative monitoring of activities of daily living (ADL) in SCI individuals with the goal of identifying cardiovascular events and PI-related risk behaviors. ADLs specific to SCI patients and their lifestyles shall be discussed and narrowed down in the scope of this work, therefore an autonomous camera-based system is proposed to classify ADLs. The Current work builds on a previous project where a SlowFast network [1] was trained to identify SCI-specific classes and we aim to further improve the classification and temporal resolution for transferring to wearables' time-series data.
Keywords
Computer vision, activity classification, video processing, Deep Learning, ADL, soft-labelling, probabilistic networks
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Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis , ETH for Development (ETH4D) (ETHZ) , ETH Zurich (ETHZ)
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Published since: 2025-03-25 , Earliest start: 2025-05-01 , Latest end: 2026-02-28
Applications limited to EPFL - Ecole Polytechnique Fédérale de Lausanne , ETH Zurich , Zurich University of the Arts , Wyss Translational Center Zurich , University of Zurich , Zurich University of Applied Sciences , CERN , CSEM - Centre Suisse d'Electronique et Microtechnique , Department of Quantitative Biomedicine , Lucerne University of Applied Sciences and Arts , Institute for Research in Biomedicine , IBM Research Zurich Lab , University of St. Gallen , University of Lucerne , University of Lausanne , University of Geneva , University of Fribourg , University of Berne , University of Basel , Université de Neuchâtel , Swiss Institute of Bioinformatics , Swiss National Science Foundation , Swiss Federal Institute for Forest, Snow and Landscape Research , Institute of Robotics and Intelligent Systems D-MAVT , TU Berlin , TU Darmstadt , TU Dresden , RWTH Aachen University , Technische Universität München , Technische Universität Hamburg , Max Planck Society , University of Oxford , University of Leeds , University of Cambridge , UCL - University College London , National Institute for Medical Research , Imperial College London , Royal College of Art , Empa , Università della Svizzera italiana , Hochschulmedizin Zürich , Hong Kong University of Science and Technology , University of Washington , Tokyo Institute of Technology , The University of Tokyo
Organization Sensory-Motor Systems Lab
Hosts Paez Diego, Dr. , Paez Diego, Dr. , Paez Diego, Dr.
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Behavioural and Cognitive Sciences
Extending Functional Scene Graphs to Include Articulated Object States
While traditional [1] and functional [2] scene graphs are capable of capturing the spatial relationships and functional interactions between objects and spaces, they encode each object as static, with fixed geometry. In this project, we aim to enable the estimation of the state of articulated objects and include it in the functional scene graph.
Keywords
scene understanding, scene graph, exploration
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Master Thesis
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Published since: 2025-03-25 , Earliest start: 2025-03-25
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Computer Vision and Geometry Group
Hosts Bauer Zuria, Dr. , Trisovic Jelena , Zurbrügg René
Topics Information, Computing and Communication Sciences , Engineering and Technology
Master Thesis: Development of a Customized Knee Orthosis for Osteoarthritis
Osteoarthritis (OA) presents a significant challenge in healthcare, necessitating innovative solutions to alleviate pain, enhance mobility. This thesis documents the research and development journey of an OA knee orthosis within the Spinal Cord and Artificial Intelligence Lab (SCAI-Lab) at ETH Zurich. This thesis is a close collaboration between the ORTHO-TEAM Group and the SCAI-Lab at ETH Zurich. The collaboration offers a unique exchange of expertise and resources between industry and academia. Together, we aim to make meaningful progress in the field of and empower students to make valuable contributions to their academic pursuits.
Keywords
Osteo Arthritis, Orthosis, Biomechanics, AI, Medical Data, Healthcare
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-03-25 , Earliest start: 2025-04-15 , Latest end: 2026-01-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa , University of Basel , University of Berne , Zurich University of Applied Sciences , Università della Svizzera italiana , Hochschulmedizin Zürich , Lucerne University of Applied Sciences and Arts , Institute for Research in Biomedicine , CSEM - Centre Suisse d'Electronique et Microtechnique
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Paez Diego, Dr. , Paez Diego, Dr.
Topics Medical and Health Sciences , Engineering and Technology
Develop Dexterous Humanoid Robotic Hands
Design and build dexterous human-like robotic hands with us at the Soft Robotics Lab and the ETH spin-off mimic. We will explore different possibilities of developing design features and sub-systems. The developed features shall be integrated into a fully functional robotic hand and applied to solve practical manipulation challenges.
Keywords
humanoid, robotics, hand, dexterity, soft robotics, actuation, prototyping, modeling and control, mechatronics, biomimetic, design, 3D printing, silicone casting, electronics, machine learning, control
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Semester Project , Master Thesis
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Published since: 2025-03-24 , Earliest start: 2025-01-01 , Latest end: 2026-03-31
Organization Soft Robotics Lab
Hosts Weirich Stefan
Topics Engineering and Technology
Advancing Space Navigation and Landing with Event-Based Camera in collaboration with the European Space Agency
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.
Keywords
event-based camera, vision-based navigation
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Master Thesis
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Published since: 2025-03-19 , Earliest start: 2025-03-23 , Latest end: 2025-12-31
Applications limited to University of Zurich , ETH Zurich
Organization Robotics and Perception
Hosts Cannici Marco , Pellerito Roberto
Topics Engineering and Technology
Time-continuous Facial Motion Capture Using Event Cameras
Traditional facial motion capture systems, including marker-based methods and multi-camera rigs, often struggle to capture fine details such as micro-expressions and subtle wrinkles. While learning-based techniques using monocular RGB images have improved tracking fidelity, their temporal resolution remains limited by conventional camera frame rates. Event-based cameras present a compelling solution, offering superior temporal resolution without the cost and complexity of high-speed RGB cameras. This project explores the potential of event-based cameras to enhance facial motion tracking, enabling the precise capture of subtle facial dynamics over time.
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-03-19 , Earliest start: 2025-03-23 , Latest end: 2025-12-31
Organization Robotics and Perception
Hosts Pellerito Roberto
Topics Engineering and Technology
Intelligent Micromachines Made from Droplet-Based Factory
We invite applications for a Master's thesis / semester project that focuses on the fabrication of microrobots with custom shapes. Using our developed droplet printing technique, this project will explore how different microrobot shapes, created by different magnetic fields and materials, influence their control behaviors in blood vessels. This research aims to advance biomedical technologies, particularly in targeted drug delivery and minimally invasive procedures.
Keywords
Microrobotics, 4D Printing, Soft Materials, Biomedical Devices
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Semester Project , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-03-18 , Earliest start: 2025-06-02
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Engineering and Technology , Chemistry
Better Scaling Laws for Neuromorphic Systems
This project explores and extends the novel "deep state-space models" framework by leveraging their transfer function representations.
Keywords
deep learning, state space models, transfer function, parameterizations, S4 model, Fourier Transform, Convolution, Neuromorphic Systems, Neuromorphic, Sequence Modeling, Event-based Vision
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Semester Project , Master Thesis
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Published since: 2025-03-18
Applications limited to University of Zurich , ETH Zurich
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Industrial Design of a Medical Robotic Platform for Autonomous Eye Injections
The purpose of this project is to enhance an existing robotic platform capable of autonomously delivering injections into the human eye. Rather than starting from zero, the student will build upon substantial prior research. The project’s primary focus is on industrial design—making the system both visually appealing and suitable for clinical settings. This includes collaborating with external manufacturers for casting and production, resulting in a polished, user-friendly device for healthcare professionals. In addition, the student will do some coding in Python (specifically for motion planning) to run experiments on porcine and mock-eyes using the updated design.
Keywords
Mechanical design, system integration, industrial design
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ETH Zurich (ETHZ)
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Published since: 2025-03-18
Organization Multiscale Robotics Lab
Hosts Ehmke Claas
Topics Engineering and Technology
Event-based feature detection for highly dynamic tracking
Event cameras are an exciting new technology enabling sensing of highly dynamic content over a broad range of illumination conditions. The present thesis explores novel, sparse, event-driven paradigms for detecting structure and motion patterns in raw event streams.
Keywords
Event camera, neuromorphic sensing, feature detection, computer vision
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Master Thesis
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Published since: 2025-03-13 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Fast, change-aware map-based camera tracking
Experiment with Gaussian Splatting based map representations for highly efficient camera tracking and simultaneous change detection and map updating. Apply to different exteroceptive sensing modalities.
Keywords
Localization, Camera Tracking, Gaussian Splatting, Change detection
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Master Thesis
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Published since: 2025-03-13 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Soft object reconstruction
This project consists of reconstructing soft object along with their appearance, geometry, and physical properties from image data for inclusion in reinforcement learning frameworks for manipulation tasks.
Keywords
Computer Vision, Structure from Motion, Image-based Reconstruction, Physics-based Reconstruction
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Master Thesis
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Published since: 2025-03-13 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Reconstruction from online videos taken in the wild
Push the limits of arbitrary online video reconstruction by combining the most recent, prior-supported real-time Simultaneous Localization And Mapping (SLAM) methods with automatic supervision techniques.
Keywords
Computer Vision, 3D Reconstruction, SLAM
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Master Thesis
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Published since: 2025-03-13 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Computationally Efficient Neural Networks
Computing, time, and energy requirements of recent neural networks have demonstrated dramatic increase over time, impacting on their applicability in real-world contexts. The present thesis explores novel ways of implementing neural network implementations that will substantially reduce their computational complexity and thus energy footprint.
Keywords
AI, CNNs, transformers, network implementation
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Master Thesis
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Published since: 2025-03-12 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Generalist Excavator Transformer
We want to develop a generalist digging agent that is able to do multiple tasks, such as digging and moving loose soil, and/or control multiple excavators. We plan to use decision transformers, trained on offline data, to accomplish these tasks.
Keywords
Offline reinforcement learning, transformers, autonomous excavation
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Semester Project , Master Thesis
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Published since: 2025-03-11 , Earliest start: 2025-03-01 , Latest end: 2025-08-31
Organization Robotic Systems Lab
Hosts Werner Lennart , Egli Pascal Arturo , Terenzi Lorenzo , Nan Fang , Zhang Weixuan
Topics Information, Computing and Communication Sciences
Differential Particle Simulation for Robotics
This project focuses on applying differential particle-based simulation to address challenges in simulating real-world robotic tasks involving interactions with fluids, granular materials, and soft objects. Leveraging the differentiability of simulations, the project aims to enhance simulation accuracy with limited real-world data and explore learning robotic control using first-order gradient information.
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Semester Project , Master Thesis
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Published since: 2025-03-10 , Earliest start: 2025-01-01 , Latest end: 2025-12-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Robotic Systems Lab
Hosts Nan Fang , Ma Hao
Topics Engineering and Technology
Wearable kirigami antenna for motion monitoring
The aim of the project is to develop a simple method for fabrication of kirigami-inspired laser-cut or molded antennas on flexible substrates. This technology will enable advancements in wearable electronics for wireless communication and sensing applications.
Keywords
wearable, flexible electronics, kirigami, laser cutting, 3D printing, antenna design, conductivity, wireless communication
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Semester Project , Bachelor Thesis
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Published since: 2025-03-09 , Earliest start: 2025-03-24 , Latest end: 2026-08-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Kateb Pierre
Topics Engineering and Technology
Soft Robot Under Ultrasound Actuation
Soft robotics has gained significant attention in recent years due to its ability to perform delicate and adaptive tasks that traditional rigid robots cannot achieve. Among various actuation methods, ultrasound-driven soft robots present a promising avenue for non-contact and precise control in liquid environments. These robots have potential applications in biomedical fields, microfluidics, and underwater exploration. The integration of ultrasound as an actuation mechanism enables efficient propulsion, controlled deformation, and complex locomotion patterns.
Keywords
ultrasound-driven soft robots
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Master Thesis
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Published since: 2025-03-07 , Earliest start: 2025-03-10 , Latest end: 2025-09-10
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Zhong Chengxi
Topics Engineering and Technology , Physics
Master Thesis: Contact force evaluation of robotic endoscopic system based on Series Elastic Actuation
In the BIROMED-Lab we have been developing an endoscopic system for safer neurosurgeries with inspiration from human finger anatomy. Its two degrees of freedom allow the endoscope to investigate areas of the brain that would be inaccessible with standard rigid endoscopes. Thanks to springs in the transmission between the motors and the movable endoscope tip, the interaction forces between the instrument and the brain tissue can be reduced. Furthermore the interaction forces can be estimated by measuring the deflection of the spring. To make the telemanipulation of the endoscope safer and more intuitive for the surgeon, force feedback was also implemented.
Keywords
Robotic surgery, Neurosurgery, Telemanipulation, Haptic feedback, Robotic endoscope
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Master Thesis
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Published since: 2025-03-06 , Earliest start: 2025-03-01
Organization Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab)
Hosts Ettori Sara Lisa Margherita , Gerig Nicolas, Dr. , Sommerhalder Michael
Topics Engineering and Technology
Development of intelligent lab-on-a-chip devices for high-throughput cell manipulation and microrobot production
Microfluidic devices can be employed in biological research as lab-on-a-chip (LoC) and organ-on-a-chip (OoC) systems. These platforms enable precise in-situ cell manipulation within a highly controlled environment. In the project, we aim to develop an intelligent LoC/OoC device featuring a flexible smart “switch”, for massive production of biohybrid microrobots and high-throughput cell manipulation and drug testing.
Keywords
Lab-on-a-chip, organ-on-a-chip, magnetic microrobot, cell manipulation
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-03-05 , Earliest start: 2025-03-10 , Latest end: 2025-12-31
Applications limited to ETH Zurich , Empa , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Basel , University of Berne , University of Fribourg , University of Geneva , University of Lausanne , University of Lucerne , University of St. Gallen , University of Zurich , Zurich University of Applied Sciences , Zurich University of the Arts , Hochschulmedizin Zürich , Lucerne University of Applied Sciences and Arts
Organization Multiscale Robotics Lab
Hosts Zhu Jiawei
Topics Engineering and Technology , Biology
Novel Winch Control for Robotic Climbing
While legged robots have demonstrated impressive locomotion performance in structured environments, challenges persist in navigating steep natural terrain and loose, granular soil. These challenges extend to extraterrestrial environments and are relevant to future lunar, martian, and asteroidal missions. In order to explore the most extreme terrains, a novel winch system has been developed for the ANYmal robot platform. The winch could potentially be used as a fail-safe device to prevent falls during unassisted traverses of steep terrain, as well as an added driven degree of freedom for assisted ascending and descending of terrain too steep for unassisted traversal. The goal of this project is to develop control policies that utilize this new hardware and enable further climbing robot research.
Keywords
Robot, Space, Climbing, Winch, Control
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-03-05 , Earliest start: 2024-10-07
Organization Robotic Systems Lab
Hosts Vogel Dylan
Topics Information, Computing and Communication Sciences , Engineering and Technology
Beyond Value Functions: Stable Robot Learning with Monte-Carlo GRPO
Robotics is dominated by on-policy reinforcement learning: the paradigm of training a robot controller by iteratively interacting with the environment and maximizing some objective. A crucial idea to make this work is the Advantage Function. On each policy update, algorithms typically sum up the gradient log probabilities of all actions taken in the robot simulation. The advantage function increases or decreases the probabilities of these taken actions by comparing their “goodness” versus a baseline. Current advantage estimation methods use a value function to aggregate robot experience and hence decrease variance. This improves sample efficiency at the cost of introducing some bias. Stably training large language models via reinforcement learning is well-known to be a challenging task. A line of recent work [1, 2] has used Group-Relative Policy Optimization (GRPO) to achieve this feat. In GRPO, a series of answers are generated for each query-answer pair. The advantage is calculated based on a given answer being better than the average answer to the query. In this formulation, no value function is required. Can we adapt GRPO towards robot learning? Value Functions are known to cause issues in training stability [3] and a result in biased advantage estimates [4]. We are in the age of GPU-accelerated RL [5], training policies by simulating thousands of robot instances simultaneously. This makes a new monte-carlo (MC) approach towards RL timely, feasible and appealing. In this project, the student will be tasked to investigate the limitations of value-function based advantage estimation. Using GRPO as a starting point, the student will then develop MC-based algorithms that use the GPU’s parallel simulation capabilities for stable RL training for unbiased variance reduction while maintaining a competitive wall-clock time.
Keywords
Robot Learning, Reinforcement Learning, Monte Carlo RL, GRPO, Advantage Estimation
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-03-05
Organization Robotic Systems Lab
Hosts Klemm Victor
Topics Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Magnetic microrobots for targeted therapies
Recent advancements in medical robotics have significantly enhanced precision and innovation in healthcare, indicating a new era of minimally invasive procedures that reduce patient complications and discomfort. In particular, the development of robots constructed from materials with elastic moduli similar to soft biological tissues offers substantial promise for biomedical applications, as their inherent mechanical compliance improves safety during procedures. This project aims to fabricate double-compartment, soft, tether-free magnetic microrobots and to investigate their locomotion strategies. Critical parameters, including shape and magnetic anisotropy, will be examined in detail. Finally, the prototypes will be loaded with a model drug and evaluated in vitro using a silicone model.
Keywords
Nanoparticles, Iron Oxide, Hydrogel, Magnetic Navigation, Anisotropy
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-03-04 , Earliest start: 2025-03-09 , Latest end: 2025-08-31
Applications limited to ETH Zurich
Organization Multiscale Robotics Lab
Hosts Pustovalov Vitaly
Topics Engineering and Technology , Earth Sciences , Chemistry
Electrical Flow-Based Graph Embeddings for Event-based Vision and other downstream tasks
This project explores a novel approach to graph embeddings using electrical flow computations.
Keywords
graph neural networks, graph representation learning, spectral graph theory, network analysis, electrical flow, event-based vision, low-dimensional graph representations
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Master Thesis
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Published since: 2025-03-04 , Earliest start: 2024-09-02
Applications limited to University of Zurich , ETH Zurich
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Behavioural and Cognitive Sciences
Leveraging Long Sequence Modeling for Drone Racing
Study the application of Long Sequence Modeling techniques within Reinforcement Learning (RL) to improve autonomous drone racing capabilities.
Keywords
long sequence modeling, state-space models, convolutional neural networks, CNNs, recurrent neural networks, RNNs, sequence dynamics, dynamical systems, reinforcement learning, RL, optimal control, drone racing, machine learning, autonomous navigation
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Master Thesis
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Published since: 2025-03-04
Applications limited to ETH Zurich , University of Zurich
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Information, Computing and Communication Sciences , Engineering and Technology
Neural Architecture Knowledge Transfer for Event-based Vision
Perform knowledge distillation from Transformers to more energy-efficient neural network architectures for Event-based Vision.
Keywords
deep neural networks, knowledge transfer, knowledge distillation, event cameras, event-based vision, sequence modeling, transformers, low-energy vision
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Master Thesis
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Published since: 2025-03-04
Applications limited to ETH Zurich , University of Zurich
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Information, Computing and Communication Sciences , Engineering and Technology
Deep Learning of Residual Physics For Soft Robot Simulation
Incorporating state-of-the-art deep learning approaches to augment conventional soft robotic simulations for a fast, accurate and useful simulation for real soft robots.
Keywords
Soft Robotics, Machine Learning, Physical Modeling, Simulation
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Semester Project , Master Thesis
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Published since: 2025-03-02 , Earliest start: 2025-03-01 , Latest end: 2026-03-01
Organization Soft Robotics Lab
Hosts Michelis Mike , Katzschmann Robert, Prof. Dr.
Topics Information, Computing and Communication Sciences , Engineering and Technology
Volumetric Bucket-Fill Estimation
Gravis Robotics is an ETH spinoff from the Robotic Systems Lab (RSL) working on the automation of heavy machinery (https://gravisrobotics.com/). In this project, you will be working with the Gravis team to develop a perceptive bucket-fill estimation system. You will conduct your project at Gravis under joint supervision from RSL.
Keywords
Autonomous Excavation
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Semester Project , Master Thesis
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Published since: 2025-02-28 , Earliest start: 2025-01-01 , Latest end: 2026-01-01
Organization Robotic Systems Lab
Hosts Egli Pascal Arturo
Topics Engineering and Technology
Master Thesis: Vibro-tactile feedback in ventricle puncturing during External Ventricular Drain (EVD) procedure
EVD is a common procedure in Neurosurgery, nevertheless its placement is non-ideal in up to 40% of the cases because of lack of hands-on experience of residents. To try and solve the issue we propose a medical simulator that will merge haptic feedback with hardware components. Vibro-tactile feedback has been proven useful in medical simulations and could give a more complete and realistic experience to the training surgeon, either as supplementary information to the force feedback or as stand alone information. In order to feed back the vibro-tactile information to the user, the haptic device has to be instrumentalized with appropriate custom-made hardware.
Keywords
Vibro-tactile feedback, Haptic feedback, Medical robotics, Surgical simulators
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Master Thesis
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Published since: 2025-02-26 , Earliest start: 2025-03-01
Organization Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab)
Hosts Gerig Nicolas, Dr. , Sommerhalder Michael , Ettori Sara Lisa Margherita
Topics Engineering and Technology
Leveraging Human Motion Data from Videos for Humanoid Robot Motion Learning
The advancement in humanoid robotics has reached a stage where mimicking complex human motions with high accuracy is crucial for tasks ranging from entertainment to human-robot interaction in dynamic environments. Traditional approaches in motion learning, particularly for humanoid robots, rely heavily on motion capture (MoCap) data. However, acquiring large amounts of high-quality MoCap data is both expensive and logistically challenging. In contrast, video footage of human activities, such as sports events or dance performances, is widely available and offers an abundant source of motion data. Building on recent advancements in extracting and utilizing human motion from videos, such as the method proposed in WHAM (refer to the paper "Learning Physically Simulated Tennis Skills from Broadcast Videos"), this project aims to develop a system that extracts human motion from videos and applies it to teach a humanoid robot how to perform similar actions. The primary focus will be on extracting dynamic and expressive motions from videos, such as soccer player celebrations, and using these extracted motions as reference data for reinforcement learning (RL) and imitation learning on a humanoid robot.
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Master Thesis
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Published since: 2025-02-25
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Kaufmann Manuel , Li Chenhao , Li Chenhao , Kaufmann Manuel , Li Chenhao
Topics Engineering and Technology
Learning Agile Dodgeball Behaviors for Humanoid Robots
Agility and rapid decision-making are vital for humanoid robots to safely and effectively operate in dynamic, unstructured environments. In human contexts—whether in crowded spaces, industrial settings, or collaborative environments—robots must be capable of reacting to fast, unpredictable changes in their surroundings. This includes not only planned navigation around static obstacles but also rapid responses to dynamic threats such as falling objects, sudden human movements, or unexpected collisions. Developing such reactive capabilities in legged robots remains a significant challenge due to the complexity of real-time perception, decision-making under uncertainty, and balance control. Humanoid robots, with their human-like morphology, are uniquely positioned to navigate and interact with human-centered environments. However, achieving fast, dynamic responses—especially while maintaining postural stability—requires advanced control strategies that integrate perception, motion planning, and balance control within tight time constraints. The task of dodging fast-moving objects, such as balls, provides an ideal testbed for studying these capabilities. It encapsulates several core challenges: rapid object detection and trajectory prediction, real-time motion planning, dynamic stability maintenance, and reactive behavior under uncertainty. Moreover, it presents a simplified yet rich framework to investigate more general collision avoidance strategies that could later be extended to complex real-world interactions. In robotics, reactive motion planning for dynamic environments has been widely studied, but primarily in the context of wheeled robots or static obstacle fields. Classical approaches focus on precomputed motion plans or simple reactive strategies, often unsuitable for highly dynamic scenarios where split-second decisions are critical. In the domain of legged robotics, maintaining balance while executing rapid, evasive maneuvers remains a challenging problem. Previous work on dynamic locomotion has addressed agile behaviors like running, jumping, or turning (e.g., Hutter et al., 2016; Kim et al., 2019), but these movements are often planned in advance rather than triggered reactively. More recent efforts have leveraged reinforcement learning (RL) to enable robots to adapt to dynamic environments, demonstrating success in tasks such as obstacle avoidance, perturbation recovery, and agile locomotion (Peng et al., 2017; Hwangbo et al., 2019). However, many of these approaches still struggle with real-time constraints and robustness in high-speed, unpredictable scenarios. Perception-driven control in humanoids, particularly for tasks requiring fast reactions, has seen advances through sensor fusion, visual servoing, and predictive modeling. For example, integrating vision-based object tracking with dynamic motion planning has enabled robots to perform tasks like ball catching or blocking (Ishiguro et al., 2002; Behnke, 2004). Yet, dodging requires a fundamentally different approach: instead of converging toward an object (as in catching), the robot must predict and strategically avoid the object’s trajectory while maintaining balance—often in the presence of limited maneuvering time. Dodgeball-inspired robotics research has been explored in limited contexts, primarily using wheeled robots or simplified agents in simulations. Few studies have addressed the challenges of high-speed evasion combined with the complexities of humanoid balance and multi-joint coordination. This project aims to bridge that gap by developing learning-based methods that enable humanoid robots to reactively avoid fast-approaching objects in real time, while preserving stability and agility.
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Master Thesis
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Published since: 2025-02-25
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Engineering and Technology
Learning Real-time Human Motion Tracking on a Humanoid Robot
Humanoid robots, designed to mimic the structure and behavior of humans, have seen significant advancements in kinematics, dynamics, and control systems. Teleoperation of humanoid robots involves complex control strategies to manage bipedal locomotion, balance, and interaction with environments. Research in this area has focused on developing robots that can perform tasks in environments designed for humans, from simple object manipulation to navigating complex terrains. Reinforcement learning has emerged as a powerful method for enabling robots to learn from interactions with their environment, improving their performance over time without explicit programming for every possible scenario. In the context of humanoid robotics and teleoperation, RL can be used to optimize control policies, adapt to new tasks, and improve the efficiency and safety of human-robot interactions. Key challenges include the high dimensionality of the action space, the need for safe exploration, and the transfer of learned skills across different tasks and environments. Integrating human motion tracking with reinforcement learning on humanoid robots represents a cutting-edge area of research. This approach involves using human motion data as input to train RL models, enabling the robot to learn more natural and human-like movements. The goal is to develop systems that can not only replicate human actions in real-time but also adapt and improve their responses over time through learning. Challenges in this area include ensuring real-time performance, dealing with the variability of human motion, and maintaining stability and safety of the humanoid robot.
Keywords
real-time, humanoid, reinforcement learning, representation learning
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Master Thesis
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Published since: 2025-02-25
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Information, Computing and Communication Sciences
Acoustic Standing Waves for Particle Manipulation in Air
Acoustic standing waves can be used to manipulate physical objects in both gas and liquid environments. This project investigates their effects on particle flow and selectivity in air, considering various particle sizes and weights. Through modeling, simulations, and experimental validation, we aim to characterize the selectivity of these waves and develop a compact driver circuit for practical implementation. The student will work closely with Honeywell engineers on test setups, electronic designs, and prototyping. A successful outcome may lead to a subsequent R&D phase or PhD project in a collaboration with Honeywellto further develop these findings.
Keywords
Acoustics, Standing Waves, Particle Manipulation, Flow Control, Electronics
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Master Thesis
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Published since: 2025-02-25 , Earliest start: 2025-02-25 , Latest end: 2025-09-30
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Medany Mahmoud
Topics Engineering and Technology , Physics
Loosely Guided Reinforcement Learning for Humanoid Parkour
Humanoid robots hold the promise of navigating complex, human-centric environments with agility and adaptability. However, training these robots to perform dynamic behaviors such as parkour—jumping, climbing, and traversing obstacles—remains a significant challenge due to the high-dimensional state and action spaces involved. Traditional Reinforcement Learning (RL) struggles in such settings, primarily due to sparse rewards and the extensive exploration needed for complex tasks. This project proposes a novel approach to address these challenges by incorporating loosely guided references into the RL process. Instead of relying solely on task-specific rewards or complex reward shaping, we introduce a simplified reference trajectory that serves as a guide during training. This trajectory, often limited to the robot's base movement, reduces the exploration burden without constraining the policy to strict tracking, allowing the emergence of diverse and adaptable behaviors. Reinforcement Learning has demonstrated remarkable success in training agents for tasks ranging from game playing to robotic manipulation. However, its application to high-dimensional, dynamic tasks like humanoid parkour is hindered by two primary challenges: Exploration Complexity: The vast state-action space of humanoids leads to slow convergence, often requiring millions of training steps. Reward Design: Sparse rewards make it difficult for the agent to discover meaningful behaviors, while dense rewards demand intricate and often brittle design efforts. By introducing a loosely guided reference—a simple trajectory representing the desired flow of the task—we aim to reduce the exploration space while maintaining the flexibility of RL. This approach bridges the gap between pure RL and demonstration-based methods, enabling the learning of complex maneuvers like climbing, jumping, and dynamic obstacle traversal without heavy reliance on reward engineering or exact demonstrations.
Keywords
humanoid, reinforcement learning, loosely guided
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Master Thesis
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Published since: 2025-02-25
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Information, Computing and Communication Sciences
Piezoelectric Atomization: Optimizing Liquid and Gel Dispersion
Piezoelectric elements are widely used for particle manipulation and atomization, with applications in humidification, cooling, and medical aerosol generation. However, temperature and environmental factors can impact the efficiency of vaporization and the properties of the generated droplets. Additionally, the heat generated by piezo elements affects particle size and flux, requiring careful control. This project will investigate the effect of piezoelectric elements on liquid and gel atomization, optimizing power consumption, repeatability, and calibration. A proof-of-concept demonstrator will be developed to study these parameters under controlled conditions. A successful outcome may lead to a subsequent R&D phase or PhD project in collaboration with Honeywell to further develop these findings
Keywords
Piezoelectric Atomization, Liquid/Gel Dispersion, Energy Efficiency, Particle Size Control, Low-Power Electronics
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Master Thesis
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Published since: 2025-02-25 , Earliest start: 2025-02-25 , Latest end: 2025-09-30
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Medany Mahmoud
Topics Engineering and Technology , Physics
Learning World Models for Legged Locomotion
Model-based reinforcement learning learns a world model from which an optimal control policy can be extracted. Understanding and predicting the forward dynamics of legged systems is crucial for effective control and planning. Forward dynamics involve predicting the next state of the robot given its current state and the applied actions. While traditional physics-based models can provide a baseline understanding, they often struggle with the complexities and non-linearities inherent in real-world scenarios, particularly due to the varying contact patterns of the robot's feet with the ground. The project aims to develop and evaluate neural network-based models for predicting the dynamics of legged environments, focusing on accounting for varying contact patterns and non-linearities. This involves collecting and preprocessing data from various simulation environment experiments, designing neural network architectures that incorporate necessary structures, and exploring hybrid models that combine physics-based predictions with neural network corrections. The models will be trained and evaluated on prediction autoregressive accuracy, with an emphasis on robustness and generalization capabilities across different noise perturbations. By the end of the project, the goal is to achieve an accurate, robust, and generalizable predictive model for the forward dynamics of legged systems.
Keywords
forward dynamics, non-smooth dynamics, neural networks, model-based reinforcement learning
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Master Thesis
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Published since: 2025-02-25
Organization Robotic Systems Lab
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Engineering and Technology
Learning Robust Agile Flight via Adaptive Curriculum
This project focuses on developing robust reinforcement learning controllers for agile drone navigation using adaptive curricula. Commonly, these controllers are trained with a static, pre-defined curriculum. The goal is to develop a dynamic, adaptive curriculum that evolves online based on the agents' performance to increase the robustness of the controllers.
Keywords
Reinforcement Learning, Drones
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Semester Project , Master Thesis
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Published since: 2025-02-21 , Earliest start: 2023-11-01 , Latest end: 2024-12-31
Organization Robotics and Perception
Hosts Xing Jiaxu
Topics Engineering and Technology
Developing Multi-Functional Microrobots Using Microfluidic Chips (3M project)
We are looking for a motivated Master’s student to join an exciting interdisciplinary thesis project, collaborating between the Multi-Scale Robotics Lab (D-MAVT) and the deMello group (D-CHAB) at ETH Zurich. This project focuses on creating a novel microfluidic-based bottom-up method to fabricate multifunctional microrobots. This innovative approach seeks to revolutionize microrobot fabrication, opening the door to diverse new applications.
Keywords
Microfluidics, Self-assembly, Microrobots
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-21 , Earliest start: 2025-02-17
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Engineering and Technology , Chemistry
Maturation Platform for Engineered 3D Muscle Tissues
The frontier of research in soft robotics aims at replacing classic soft materials used for actuators with biological ones (muscle) to take advantage of the innate adaptability, energy efficiency, and softness of biological systems. To grow more performant muscle tissues for robotics, we need to engineer a maturation platform for the muscle tissues that can provide the necessary mechanical and electrical cues. Therefore, in this project, we will aim to engineer a maturation platform for skeletal muscle bioactuators. The maturation platform will work as a device that applies cyclic stretch to the growing skeletal muscle tissue by pneumatic actuation. An initial prototype of the maturation platform has already been designed (see image). Your project will start from this prototype and do further optimization to result in a system that can give multiple stretching inputs to different muscle tissues.
Keywords
biohybrid robotics, soft robotics, 3D printing, biomaterials, actuation, material characterization
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-19 , Earliest start: 2025-02-20 , Latest end: 2025-10-31
Applications limited to EPFL - Ecole Polytechnique Fédérale de Lausanne , ETH Zurich , Empa , IBM Research Zurich Lab , University of Zurich
Organization Soft Robotics Lab
Hosts Balciunaite Aiste , Katzschmann Robert, Prof. Dr.
Topics Engineering and Technology
Design and Force-feedback Control of a Robotic Platform for Autonomous Eye Injections
The objective of this project is to advance an existing robotic platform capable of autonomously delivering injections into the human eye. Rather than starting from scratch, the student will build on significant prior research. The primary task is to implement a force-feedback control algorithm that acts as the system’s safety mechanism. Specifically, the student will develop an admittance control algorithm, enabling the robot to adapt to unexpected disturbances by using real-time data from a 6D eye-tracking device and a force sensor.
Keywords
feedback control, admittance control, industrial design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-19
Organization Multiscale Robotics Lab
Hosts Ehmke Claas
Topics Engineering and Technology
Design and Force-feedback Control of a Robotic Platform for Autonomous Eye Injections
The objective of this project is to advance an existing robotic platform capable of autonomously delivering injections into the human eye. Rather than starting from scratch, the student will build on significant prior research. The primary task is to implement a force-feedback control algorithm that acts as the system’s safety mechanism. Specifically, the student will develop an admittance control algorithm, enabling the robot to adapt to unexpected disturbances by using real-time data from a 6D eye-tracking device and a force sensor.
Keywords
feedback control, compliance control, industrial design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-19 , Earliest start: 2025-02-20
Organization Multiscale Robotics Lab
Hosts Ehmke Claas
Topics Engineering and Technology
Exploring upper limb impairments using explainable AI on Virtual Peg Insertion Test data
This thesis aims to apply explainable AI techniques to analyze time series data from the Virtual Peg Insertion Test (VPIT), uncovering additional metrics that describe upper limb impairments in neurological subjects, such as those with stroke, Parkinson's disease, and multiple sclerosis. By preserving the full dimensionality of the data, the project will identify new patterns and insights to aid in understanding motor dysfunctions and support rehabilitation.
Keywords
Machine learning, rehabilitation, neurology, upper limb, impairment, explainable AI, SHAP, novel technology, assessment, computer vision, artificial intelligence
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Master Thesis
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Published since: 2025-02-18 , Earliest start: 2025-03-09
Organization Rehabilitation Engineering Lab
Hosts Domnik Nadine
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Comparing the Virtual Peg Insertion Test (VPIT) with the haptic device Inverse3 for assessing upper limb function
This thesis will compare the Virtual Peg Insertion Test (VPIT) with the Inverse3 haptic device by Haply to evaluate its effectiveness as a tool for assessing upper limb function. The focus will be on comparing both the hardware features and software capabilities to determine if the Inverse3 can serve as a valid alternative to VPIT for clinical assessments.
Keywords
Haptic device, virtual environment, rehabilitation, programming, health technology, assessment, software, hardware
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Published since: 2025-02-18 , Earliest start: 2025-03-16
Organization Rehabilitation Engineering Lab
Hosts Domnik Nadine
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Development of Core@Shell Magnetoelectric Nanoparticles for Targeted Brain Stimulation
Magnetoelectric materials are highly promising in biomedicine with their unique ability to couple magnetic and electric fields. This coupling allows remote and precise control of various biological processes. For instance, in drug delivery, magnetoelectric nanoparticles can be directed to specific locations in the body using an external magnetic field, followed by electrical stimulation to trigger the release of therapeutic agents. The responsiveness and multifunctionality make magnetoelectric nanoparticles versatile tools in advancing non-invasive medical treatments and targeted therapies.
Keywords
Surface engineering, Nanoparticles, Iron oxide, Barium titanate, Brain Stimulation
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-18 , Earliest start: 2025-02-24 , Latest end: 2025-06-01
Applications limited to ETH Zurich
Organization Multiscale Robotics Lab
Hosts Pustovalov Vitaly
Topics Engineering and Technology , Chemistry
Solvothermal Synthesis of Metal Ferrite Nanoparticles for Small-Scale Robotic Applications
Metal ferrite nanoparticles have gathered attention due to their promising characteristics for biomedical applications, such as targeted drug delivery or diagnostics. Nanoparticle properties (e.g., morphology, size, magnetic response) play a critical role to enhance their efficacy during the application. On the other hand, reproducibility is still a considerable challenge in most of the synthesis approaches.
Keywords
Nanoparticles, Magnetism, Microrobotics, Iron oxide
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-18 , Earliest start: 2025-02-24 , Latest end: 2025-06-01
Applications limited to ETH Zurich
Organization Multiscale Robotics Lab
Hosts Pustovalov Vitaly
Topics Engineering and Technology , Chemistry
Multi-Sensor Semantic Odometry
Semantic segmentation augments visual information from cameras or geometric information from LiDARs by classifying what objects are present in a scene. Fusing this semantic information with visual or geometric sensor data can improve the odometry estimate of a robot moving through the scene. Uni-modal semantic odometry approaches using camera images or LiDAR point clouds have been shown to outperform traditional single-sensor approaches. However, multi-sensor odometry approaches typically provide more robust estimation in degenerate environments.
Keywords
Odometry, Sensor fusion, Semantics
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Semester Project , Master Thesis
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Published since: 2025-02-17 , Earliest start: 2024-07-14 , Latest end: 2025-01-31
Applications limited to ETH Zurich
Organization Autonomous Systems Lab
Hosts Chli Margarita , Mascaro Rubén
Topics Information, Computing and Communication Sciences
LiDAR-Visual-Inertial Odometry with a Unified Representation
Lidar-Visual-Inertial odometry approaches [1-3] aim to overcome the limitations of the individual sensing modalities by estimating a pose from heterogenous measurements. Lidar-inertial odometry often diverges in environments with degenerate geometric structures and visual-inertial odometry can diverge in environments with uniform texture. Many existing lidar-visual-inertial odometry approaches use independent lidar-inertial and visual-inertial pipelines [2-3] to compute odometry estimates that are combined in a joint optimisation to obtain a single pose estimate. These approaches are able to obtain a robust pose estimate in degenerate environments but often underperform lidar-inertial or visual-inertial methods in non-degenerate scenarios due to the complexity of maintaining and combining odometry estimates from multiple representations.
Keywords
Odometry, SLAM, Sensor Fusion
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Semester Project , Master Thesis
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Published since: 2025-02-17 , Earliest start: 2025-01-05 , Latest end: 2025-06-30
Applications limited to ETH Zurich
Organization Autonomous Systems Lab
Hosts Mascaro Rubén , Chli Margarita
Topics Information, Computing and Communication Sciences
Odometry and Mapping in Dynamic Environments
Existing lidar-inertial odometry approaches (e.g., FAST-LIO2 [1]) are capable of providing sufficiently accurate pose estimation in structured environments to capture high quality 3D maps of static structures in real-time. However, the presence of dynamic objects in an environment can reduce the accuracy of the odometry estimate and produce noisy artifacts in the captured 3D map. Existing approaches to handling dynamic objects [2-4] focus on detecting and filtering them from the captured 3D map but typically operate independently from the odometry pipeline, which means that the dynamic filtering does not improve the pose estimation accuracy.
Keywords
Odometry, Mapping, SLAM, Dynamic Environments
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Semester Project , Master Thesis
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Published since: 2025-02-17 , Earliest start: 2025-01-05 , Latest end: 2025-06-30
Applications limited to ETH Zurich
Organization Autonomous Systems Lab
Hosts Mascaro Rubén , Chli Margarita
Topics Information, Computing and Communication Sciences , Engineering and Technology
Embedded algorithms of IMUs in a neurorehabilitation device
The goal of this project is to help develop embedded firmware for a imu based rehabilitation device. This project is part of the SmartVNS project which utilizes movement-gated control of vagus nerve stimulation for stroke rehabilitation.
Keywords
electrical engineering PCB Embedded systems neurorehabilitation
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Semester Project , Master Thesis
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Published since: 2025-02-14 , Earliest start: 2024-01-06 , Latest end: 2024-12-31
Organization Rehabilitation Engineering Lab
Hosts Donegan Dane , Viskaitis Paulius
Topics Medical and Health Sciences , Engineering and Technology
Analysis and modelling of Neurophysiological Data from Multisensory Recordings during aVNS Experiments
Join our research project focused on analysing complex neurophysiological data collected during non-invasive brain stimulation experiments. This project aims to optimise brain stimulation protocols for future stroke rehabilitation by investigating neural responses to various stimulation parameters. The data includes electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmography (PPG), inertial measurement unit (IMU) readings, pupilometry, and galvanic skin response (GSR). We aim to model brain states based on these measurements to define brain circuitry outcomes from stimulation and movement interactions, using advanced techniques like connectivity-based biomarkers. This modeling will help generalise findings to broader brain states, such as valence, attention, and stress.
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Master Thesis
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Published since: 2025-02-14 , Earliest start: 2024-08-18 , Latest end: 2025-04-30
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Medical and Health Sciences , Mathematical Sciences , Information, Computing and Communication Sciences
Jellyfish Robot Design and Acoustically Assisted Motion Control Using AI
Jellyfish-inspired robots have gained significant attention in soft robotics and biomimetic engineering due to their energy efficiency, silent propulsion, and adaptability to aquatic environments. The AI-powered Jellyfish robots offer a promising avenue for developing next-generation robotic systems with applications in biomedical research, environmental monitoring, and marine life interaction.
Keywords
AI-powered soft robotics, Jellyfish-inspired locomotion, Acoustically assisted propulsion, Machine learning-based motion control.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-14 , Earliest start: 2025-02-17 , Latest end: 2025-07-31
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Zhong Chengxi
Topics Engineering and Technology
Ultrasound Transducer Array based Helmet for Transcranial Therapy
Ultrasound-based transcranial therapy is emerging as a non-invasive and highly precise technique for treating neurological disorders, enhancing drug delivery, and promoting brain stimulation. By leveraging an advanced ultrasound transducer array embedded in a wearable helmet, this project aims to develop a novel system for targeted, real-time brain therapy
Keywords
Transcranial ultrasound therapy, Steering ultrasound field, Ultrasound transducer array design.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-14 , Earliest start: 2025-02-17 , Latest end: 2025-07-31
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Zhong Chengxi
Topics Medical and Health Sciences , Engineering and Technology
Improving SLAM in the Operating Room Using Event Cameras
This project focuses on enhancing SLAM (Simultaneous Localization and Mapping) in operating rooms using event cameras, which outperform traditional cameras in dynamic range, motion blur, and temporal resolution. By leveraging these capabilities, the project aims to develop a robust, real-time SLAM system tailored for surgical environments, addressing challenges like high-intensity lighting and head movement-induced motion blur.
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Semester Project , Master Thesis
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Published since: 2025-02-13 , Earliest start: 2025-01-13 , Latest end: 2026-01-13
Applications limited to ETH Zurich , University of Zurich , Balgrist Campus
Organization Robotics and Perception
Hosts Cannici Marco , Fürnstahl Philipp, Prof. Dr.
Topics Information, Computing and Communication Sciences , Engineering and Technology
Development of a linear electrostatic film actuator for a Humanoid Robotic Hand
Development of a linear electrostatic film actuator for soft robotic applications such as the actuation of a humanoid robotic hand.
Keywords
Electrostatic, Linear actuator, Flexible electronics, Soft Robotics, Humanoid Robotic Hands
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Master Thesis
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Published since: 2025-02-13 , Earliest start: 2025-02-23 , Latest end: 2025-12-31
Organization Soft Robotics Lab
Hosts Katzschmann Robert, Prof. Dr.
Topics Engineering and Technology
Design and Fabrication of Dexterous, Humanoid Robotic Hand
Design and build dexterous human-like robotic hands with us at the Soft Robotics Lab and the spin-off mimic. We will explore different possibilities of developing design features such as tendon-driven mechanisms, lightweight structures, and complex mechanical joints of the hand. The developed features shall be integrated into a fully functional robotic hand and applied to solve practical manipulation challenges.
Keywords
humanoid, robotics, hand, dexterity, soft robotics, actuation, prototyping, modeling and control, mechatronics, biomimetic, design, 3D printing, silicone casting
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-13 , Earliest start: 2024-09-01 , Latest end: 2025-07-24
Organization Soft Robotics Lab
Hosts Hinchet Ronan , Katzschmann Robert, Prof. Dr. , Weirich Stefan
Topics Engineering and Technology
Feasibility of RehabCoach on Adherence to Unsupervised Robot-Assisted Therapy – Implementation and Evaluation of Smart Reminders
Adherence to rehabilitation therapy is essential for the recovery of hand functionality in stroke and traumatic brain injury (TBI) patients. However, maintaining engagement outside clinical settings remains a challenge. This project involves a feasibility study to evaluate the adherence of patients using the RehabCoach app as part of a one-week unsupervised robot-assisted program simulation. The study assesses user engagement, app interaction patterns, and the effectiveness of push notifications/smart reminders in sustaining adherence to the training program. The key components of this research are the development of a smart algorithm for triggering push notifications based on specific user behaviors, such as therapy completion or inactivity, to optimize adherence, as well as conducting the study with a few participants.
Keywords
Stroke, Traumatic Brain Injury, Rehabilitation Therapy, Adherence, Push Notifications, Mobile Health App, Interdisciplinary Research, Python, Django
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-12 , Earliest start: 2025-02-16 , Latest end: 2025-11-30
Organization Rehabilitation Engineering Lab
Hosts Retevoi Alexandra
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Benefits and challenges of promoting minimally supervised therapy in a rehabilitation clinic
Increasing the therapy time can benefit patients in multiple ways. Group therapy (e.g., technology-assisted) allows clinics to increase the therapy dose for patients without increasing the workload for therapists. However, in practical implementation, some challenges often arise (e.g., patients not liking it) that limit the efficacy of group therapy. The aim of this project is to gain practical experience with group therapy sessions (i.e., supporting group therapy sessions at the Clinica Hildebrand in Brissago), identify barriers and benefits related to group therapy, and propose guidelines to improve the integration of group therapy in clinical practice.
Keywords
practical internship, research internship, clinical work, technology-assisted therapy, group therapy, minimally supervised therapy
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Internship
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Published since: 2025-02-12 , Earliest start: 2025-03-01 , Latest end: 2025-10-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Università della Svizzera italiana
Organization Rehabilitation Engineering Lab
Hosts Devittori Giada
Topics Medical and Health Sciences
Generating Realistic Event Camera Data with Generative AI
In this project, the student applies concepts from current advances in image generation to create artificial events from standard frames. Multiple state-of-the-art deep learning methods will be explored in the scope of this project.
Keywords
Computer Vision, Event Cameras, Deep Learning
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Semester Project , Master Thesis
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Published since: 2025-02-10 , Earliest start: 2024-12-12
Organization Robotics and Perception
Hosts Messikommer Nico
Topics Information, Computing and Communication Sciences
Enhancing Robotic Motor Policies with Event Cameras
The goal of this project is to develop a shared embedding space for events and frames, enabling the training of a motor policy on simulated frames and deployment on real-world event data.
Keywords
Computer Vision, Event Cameras, Robotics, Unsupervised Domain Adaption
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Semester Project , Master Thesis
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Published since: 2025-02-10 , Earliest start: 2024-12-12
Organization Robotics and Perception
Hosts Messikommer Nico
Topics Information, Computing and Communication Sciences
Generating Detailed 3D Objects from Rough 3D Primitives
This project focuses on the generation of detailed 3D models from a user-specified set of 3D cuboids.
Keywords
Generative 3D Modelling, Diffusion Models, 3D Vision
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-10 , Earliest start: 2025-02-10 , Latest end: 2025-11-30
Organization Autonomous Systems Lab
Hosts Claessens Liesbeth
Topics Information, Computing and Communication Sciences
Supervised learning for loco-manipulation
To spot arm operations, we propose a multi-phase approach combining supervised learning and reinforcement learning (RL). First, we will employ supervised learning to develop a model for solving inverse kinematics (IK), enabling precise joint angle calculations from desired end-effector pose. Next, we will utilize another supervised learning technique to build a collision avoidance model, trained to predict and avoid self-collisions based on arm configurations and environmental data. With these pre-trained networks, we will then integrate RL to generate dynamic and safe arm-motion plans. The RL agent will leverage the IK and collision avoidance models to optimize arm trajectories, ensuring efficient and collision-free movements. This entire pipeline could be back propagated while promising to enhance the accuracy, safety, and flexibility of robotic arm operations in complex environments.
Keywords
Spot, Supervised learning, loco-manipulation
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-10 , Earliest start: 2025-02-10 , Latest end: 2026-03-01
Organization Robotic Systems Lab
Hosts Mirrazavi Sina
Topics Information, Computing and Communication Sciences
Model-Based Reinforcement Learning for Loco-manipulation
This project aims to develop a model-based reinforcement learning (RL) framework to enable quadruped robots to perform dynamic locomotion and manipulation simultaneously by leveraging advanced model-based RL algorithms such as DeamerV3, TDMPC2 and SAM-RL. We will develop control policies that can predict future states and rewards, enabling the robot to adapt its behavior on-the-fly. The primary focus will be on achieving stable and adaptive walking patterns while reaching and grasping objects. The outcome will provide insights into the integration of complex behaviors in robotic systems, with potential applications in service robotics and automated object handling.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-10 , Earliest start: 2025-02-10 , Latest end: 2026-02-10
Organization Robotic Systems Lab
Hosts Mirrazavi Sina
Topics Information, Computing and Communication Sciences
Integrating OpenVLA for Vision-Language-Driven Loco-Manipulation robotics scenarios
This thesis proposes to integrate and adapt the OpenVLA (Open-Source Vision-Language-Action) model to control the Spot robotic arm for performing complex grasping and placing tasks. The study will focus on enabling the robot to recognize, grasp, and organize various toy-sized kitchen items based on human instructions. By leveraging OpenVLA's robust multimodal capabilities, this project aims to bridge the gap between human intent and robotic actions, enabling seamless task execution in unstructured environments. The research will explore the feasibility of fine-tuning OpenVLA for task-specific operations and evaluate its performance in real-world scenarios, providing valuable insights for advancing multimodal robotics.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-10 , Earliest start: 2025-02-10 , Latest end: 2026-02-10
Organization Robotic Systems Lab
Hosts Mirrazavi Sina
Topics Information, Computing and Communication Sciences
Differentiable Simulation for Precise End-Effector Tracking
Unlock the potential of differentiable simulation on ALMA, a quadrupedal robot equipped with a robotic arm. Differentiable simulation enables precise gradient-based optimization, promising greater tracking accuracy and efficiency compared to standard reinforcement learning approaches. This project dives into advanced simulation and control techniques, paving the way for improvements in robotic trajectory tracking.
Keywords
Differentiable Simulation, Learning, ALMA
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-07 , Earliest start: 2025-01-27
Organization Robotic Systems Lab
Hosts Mittal Mayank , Schwarke Clemens , Klemm Victor
Topics Information, Computing and Communication Sciences
Research Assistant in Biosensing for Robotics Care and Body Simulation (~12 months)
Join a team of scientists improving the long-term prognosis and treatment of Spinal Cord Injury (SCI) through mobile and wearable systems and personalized health monitoring. Joining the SCAI Lab part of the Sensory-Motor Systems Lab at ETH, you will have the unique opportunity of working at one of the largest and most prestigious health providers in Switzerland: Swiss Paraplegic Center (SPZ) in Nottwil (LU).
Keywords
App development, Machine Learning, Data bases, Data engineering, Systems Engineering, Data Modelling
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Internship , Lab Practice , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-02-06 , Earliest start: 2025-03-03 , Latest end: 2026-12-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , IBM Research Zurich Lab , Institute for Research in Biomedicine , Hochschulmedizin Zürich , Swiss Institute of Bioinformatics , University of Lucerne , University of Zurich , Zurich University of Applied Sciences , Zurich University of the Arts , Lucerne University of Applied Sciences and Arts , Berner Fachhochschule
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Paez Diego, Dr. , Paez Diego, Dr. , Paez Diego, Dr.
Topics Information, Computing and Communication Sciences
Master's Thesis: AI-powered nap detection from Fitbit data
The uprise of consumer-grade fitness trackers has opened the doors to long-term activity monitoring in the wild in research and clinics. However, Fitbit does not identify napping episodes shorter than 90 minutes. Hence, there is a need to establish a robust algorithm to detect naps.
Keywords
Data analysis, machine learning, signal processing, wearables, Fitbit, naps detection
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Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-06 , Earliest start: 2025-02-10 , Latest end: 2025-08-31
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Gnarra Oriella , Gnarra Oriella
Topics Information, Computing and Communication Sciences , Engineering and Technology
Modeling and Simulation for Earthwork in Digital Twin
In this work, we aim to build a digital twin of our autonomous hydraulic excavator, leveraging Mathworks technology for high-fidelity modeling. This will be used in the future to test and benchmark our learning-based controllers.
Keywords
Modeling, Hydraulics, Excavation, Industry
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-02-06 , Earliest start: 2025-03-03
Organization Robotic Systems Lab
Hosts Spinelli Filippo , Nan Fang
Topics Information, Computing and Communication Sciences , Engineering and Technology
Untethered ultrafast-rotating spiral microrobot for physical thrombolysis
The ability to manipulate micro-scale objects with precision is a growing field in biomedical engineering, particularly in the context of treating thrombotic conditions. Thrombolysis, the process of dissolving blood clots, remains a significant challenge in medical treatment, with current techniques often limited by their invasiveness and effectiveness. Recent advancements have explored the use of microrobots for targeted thrombolysis, leveraging their ability to maneuver in complex biological environments to enhance clot dissolution and drug delivery. Rotation plays a crucial role in various natural processes, including feeding and locomotion, demonstrating its effectiveness in achieving complex interactions with the environment. However, achieving ultrafast rotation in artificial microrobots presents significant engineering challenges. Traditional methods of inducing rotation, such as acoustic manipulation, have shown promise but are often constrained by limitations in rotational speed and control precision. These constraints hinder the microrobot's ability to effectively engage with functions. In response to these challenges, we introduce an innovative solution: an untethered ultrafast-rotating spiral microrobot designed for physical thrombolysis. This microrobot employs a symmetric spiral structure that generates a consistent torque while maintaining a zero net force, allowing for sustained high-speed rotation. The unique design of the spiral structure ensures efficient rotational motion, overcoming previous limitations in rotation speed. A key feature of our microrobot is its sharp-tip design, which enhances its ability to penetrate and mechanically disrupt thrombi. This mechanical drilling action facilitates the breakdown of clots, making thrombolysis more effective. Additionally, the microrobot incorporates a drug-holding cavity, enabling it to deliver therapeutic agents directly to the site of the thrombus. This dual functionality—mechanical disruption combined with targeted drug delivery—promises a more efficient approach to thrombolysis. This ultrafast-rotating microrobot represents a significant advancement in microrobot design and its application in medical treatments.
Keywords
Keywords: Rotation; acoustic microrobot; thrombolysis
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Master Thesis
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Published since: 2025-02-05 , Earliest start: 2025-02-06 , Latest end: 2025-09-30
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Deng Yong
Topics Engineering and Technology
Designing Freeform Trajectories through Acoustic Streaming and Artificial Intelligence
The manipulation of materials and fluids through acoustic streaming has emerged as a powerful technique with applications in manufacturing and biomedical engineering. This method utilizes sound waves to control the movement of particles within a fluid, offering precise and non-invasive manipulation. However, achieving freeform path manipulation—guiding materials along complex, non-linear trajectories—remains a significant challenge due to difficulties in controlling the influence range and vortex dynamics of acoustic streaming. Traditional methods often struggle with maintaining precision and stability along intricate paths, as the non-uniform distribution of acoustic forces complicates consistent directionality. Artificial Intelligence (AI) presents a promising solution, enabling real-time control and optimization of these systems. By integrating AI with acoustic streaming, algorithms can analyze and predict the interactions between acoustic forces and fluid dynamics, allowing for dynamic adjustments that enhance accuracy. In this thesis, we propose addressing these challenges by implementing a pillar array of acoustic actuators coupled with AI-driven control systems. The pillar array will generate and modulate acoustic streaming fields, while AI will optimize and automate their control in real time. This integration aims to improve the precision of freeform path manipulation, facilitating the creation of complex patterns that are otherwise difficult to achieve, thereby expanding the possibilities for material manipulation across various applications.
Keywords
Freeform path; Manipulation; Ultrasound; pillar array; AI
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-05 , Earliest start: 2025-02-06 , Latest end: 2025-09-30
Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)
Hosts Deng Yong
Topics Engineering and Technology
Computational Modeling of Muscle Dynamics for Biohybrid Robots
This research aims to advance biohybrid robotics by integrating living biological components with artificial materials. The focus is on developing computational models for artificial muscle cells, a critical element in creating biohybrid robots. Challenges include modeling the complex and nonlinear nature of biological muscles, considering factors like elasticity and muscle fatigue, as well as accounting for fluid-structure interaction in the artificial muscle's environment. The research combines first principle soft body simulation methods and machine learning to improve understanding and control of biohybrid systems.
Keywords
Biohybrid Robotics, Computational Models, Soft Body Simulation, Finite Element Method (FEM), Muscle Dynamics, Soft Robotics
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01
Organization Soft Robotics Lab
Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Biology , Physics
GPU Acceleration of Soft Robot Modeling: Enhancing Performance with CUDA
We are enhancing soft robot modeling by developing a GPU-accelerated version of our FEM-based framework using CUDA. This research focuses on optimizing parallel computations to significantly speed up simulations, enabling larger problem sizes and real-time control. By improving computational efficiency, we aim to advance soft robotics research and facilitate more detailed, dynamic simulations.
Keywords
Soft Body Simulation, high-performance computing, GPU programming, Parallel Computing, Finite Element Method (FEM), Multiphysics Simulation
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01
Organization Soft Robotics Lab
Hosts Katzschmann Robert, Prof. Dr. , Mekkattu Manuel
Topics Information, Computing and Communication Sciences , Engineering and Technology
Advancing Soft Robot Modeling: Integrating Physics, Optimization, and Control
We are advancing soft robot simulation with FEM and energy-based methods to model complex, adaptive behaviors. This research entails developing the framework to support diverse designs, integrate new physics models, and optimize performance, enabling enhanced control and real-world applications of soft robots.
Keywords
Soft Robotics, Finite Element Method (FEM), Physical Modeling, Benchmarking, Optimization, Multiphysics Simulation, Sim-to-Real
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01
Organization Soft Robotics Lab
Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.
Topics Information, Computing and Communication Sciences , Engineering and Technology
Reinforcement Learning for Excavation Planning In Terra
We aim to develop a reinforcement learning-based global excavation planner that can plan for the long term and execute a wide range of excavation geometries. The system will be deployed on our legged excavator.
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Keywords: Reinforcement learning, task planning
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-04-01 , Latest end: 2025-08-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Model Based Reinforcement Learning
We want to train an excavator agent to learn in a variety of soil using a fast, GPU-accelerated soil particle simulator in Isaac Sim.
Keywords
particle simulation, omniverse, warp, reinforcement learning, model based reinforcement learning.
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-02-28 , Latest end: 2025-08-31
Organization Robotic Systems Lab
Hosts Egli Pascal Arturo , Terenzi Lorenzo
Topics Information, Computing and Communication Sciences , Engineering and Technology
Reinforcement Learning for Particle-Based Excavation in Isaac Sim
We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim.
Keywords
particle simulation, omniverse, warp, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-04-01 , Latest end: 2025-09-30
Organization Robotic Systems Lab
Hosts Egli Pascal Arturo , Mittal Mayank , Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Perceptive Reinforcement Learning for Exavation
In this project, our goal is to leverage precomputed embeddings(VAE in Isaacsim) from 3D earthworks scene reconstructions to train reinforcement learning agents. These embeddings, derived from incomplete point cloud data and reconstructed using an encoder-decoder neural network, will serve as latent representations. The main emphasis is on utilizing these representations to develop and train reinforcement learning policies for digging tasks.
Keywords
LIDAR, 3D reconstruction, Isaac gym, deep learning, perception, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-04-01 , Latest end: 2025-08-31
Organization Robotic Systems Lab
Hosts Höller David , Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Reiforcement Learning of Pretrained Trasformer Models
We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim.
Keywords
Keywords: particle simulation, omniverse, warp, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-04-01 , Latest end: 2025-08-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Multiagent Reinforcement Learning in Terra
We want to train multiple agents in the Terra environment, a fully end-to-end GPU-accelerated environment for RL training.
Keywords
multiagent reinforcement learning, jax, deep learning, planning
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Semester Project , Master Thesis
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Published since: 2025-02-03 , Earliest start: 2025-04-01 , Latest end: 2025-09-16
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences