Projects and Theses
Multimodal Clinical Modeling on UK Biobank
This project aims to build a deep learning baseline model on the UK Biobank dataset, including multimodal data extraction and predictive modeling, and to explore practical solutions to data sparsity—laying the foundation for future large-scale clinical models. We are looking for a Master student to conduct either a Master Thesis or Semester Thesis at ETH Zurich for this work. Exceptionally motivated students are also welcome to join as research interns, depending on availability and fit.
Keywords
deep learning, Multimodal learning, LLM, foundation model, clinical data
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Semester Project , Internship , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-14 , Earliest start: 2025-08-01 , Latest end: 2026-03-01
Organization Sensory-Motor Systems Lab
Hosts Guo Wen
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Gait Capacity and Performance Assessment in Stroke
Our primary objective is to validate population specific IMU algorithms to measure gait performance at home and further investigate the relationship between gait capacity and gait performance in patients after discharge from a rehabilitation clinic.
Keywords
Gait, rehabilitation, IMU, data analysis
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Internship , Lab Practice , Master Thesis
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Published since: 2025-07-14 , Earliest start: 2025-08-01 , Latest end: 2026-08-01
Organization Rehabilitation Engineering Lab
Hosts Berthet Mathieu
Topics Engineering and Technology
Marker displacement error correction for joint kinematics
Accurate estimation of joint kinematics is essential in longitudinal gait studies. However errors in marker placement used to track joint movement can confound clinical interpretation and obscure true physiological change. This project aims to develop and validate a correction pipeline that mitigates the kinematic errors introduced by marker displacement.
Keywords
Kinematics, data analysis, rehabilitation, clinical study
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Internship , Lab Practice
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Published since: 2025-07-14 , Earliest start: 2025-09-01 , Latest end: 2026-04-01
Organization Rehabilitation Engineering Lab
Hosts Berthet Mathieu
Topics Engineering and Technology
Tracking and Modeling Recovery in Stroke and Parkinson’s Disease Rehabilitation
We are seeking a motivated and detail-oriented student to join our clinical research team for a project focused on analyzing and refining clinical gait data. In clinical gait analysis, tracking patient progress from day to day is essential for assessing rehabilitation and treatment outcomes. To do this, we want to develop a reliable predictive model to support this process. It should integrate diverse and complex data, including biomechanical, physiological, and contextual variables.
Keywords
Rehabilitation, gait, data analysis, clinical trial, measurement
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-14 , Earliest start: 2025-08-01 , Latest end: 2026-06-01
Organization Rehabilitation Engineering Lab
Hosts Berthet Mathieu
Topics Engineering and Technology
Editing Benchmarking RISC-V-based Accelerators for Embodied AI and Robotics
In this project we want to run both clasical CV networks (like YOLO) and SoA small Large Language Models (LLMs) on a new cutting edge risc-v accelerator from Axelera. Ultimately, we want to build a compact embedded setup to enable embodied AI for robotics
Keywords
Embodied AI, embedded programming, LLM, Convolutional neural networks, robotics, efficient CNN deployment.
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-14 , Earliest start: 2025-08-01 , Latest end: 2026-05-31
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Information, Computing and Communication Sciences , Engineering and Technology
3D motion generation for children with walking disabilities via deep learning
This project is part of a broader research project at ETH Zurich that focuses on studying the gait of children with walking disabilities, such as those with cerebral palsy (CP), and to support the design of simple, personalized, and low-cost orthosis devices. Most existing motion research focuses on healthy adults, while studies and data on children with impaired gait are very limited. This thesis focuses on building a generative model that predicts corrected motion of a CP children, trained with our collected 3D motion data. Specifically, the thesis consists of two main components: (1) 30% – Dataset: You will support the construction of a high-quality 3D motion dataset. As data protocols are already in place and the first data samples have been processed and are ready to use at the start of the thesis, you only need to join the ongoing data collection team to assist with some simple tasks (e.g., platform operation, basic data preprocessing and cleaning). No prior experience of data collection is required, and you will receive complete training and support. (2) 70% – Model development: You will develop a generative model (e.g., diffusion model) trained on the collected dataset. The model will take as input the uncorrected gait and generate the corrected motion with orthosis parameters, simulating the effect of using an orthosis. The project is hosted by SCAI-Lab (https://scai.ethz.ch/) within SMS Lab ( https://sms.hest.ethz.ch/) at ETHZ, and is in close collaboration with AIT Lab (https://ait.ethz.ch/). This project is looking for a Master student to conduct either a Master Thesis or Semester Thesis at ETH Zurich. Exceptionally motivated students are also welcome to join as research interns, depending on availability and fit.
Keywords
3d human motion, deep learning, generative model, ai for healthcare
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Semester Project , Internship , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-14 , Earliest start: 2025-08-01 , Latest end: 2026-03-01
Organization Sensory-Motor Systems Lab
Hosts Guo Wen
Topics Information, Computing and Communication Sciences , Engineering and Technology
See Local, Think Global: Learning Terrain Changes for Robot Navigation
Many applications, such as wildlife monitoring or search and rescue, require agents to navigate long distances autonomously. Satellite data often provides valuable information on global traversability costs for initial path planning. However, when a robot hikes and observes the terrain locally, it can detect changes - such as fresh snow or muddy slopes - that significantly change the prior cost estimate. These changes are often not only relevant for the immediate surroundings of the robot, but have broader implications, such as full valleys being covered in snow. This motivates the need to propagate these local observations to improve global maps. The robot hereby does not need to do this blindly based on current experiences, but can utilize outdated satellite data to inform its prediction.
Keywords
Satellite Time-Series, Learning-based, Deep Learning, Spatio-Temporal Modeling, Generative Models, Remote Sensing, Legged Robotics
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Semester Project , Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-08-01 , Latest end: 2026-04-30
Organization Robotic Systems Lab
Hosts Cramariuc Andrei , Richter Julia
Topics Information, Computing and Communication Sciences , Engineering and Technology
Hand Gesture Recognition Using High-Density Surface Electromyography (HD-sEMG
The project aims to develop machine learning models for real-time hand gesture recognition using high-density surface electromyography (HD-sEMG) signals. This research focuses on improving neuroprosthetic control and rehabilitation by accurately decoding hand movements from HD-sEMG data.
Keywords
HD-sEMG, neuroprosthetics, biosignal monitoring, machine learning, hand gesture recognition, rehabilitation
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ETH Zurich (ETHZ)
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Published since: 2025-07-11
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Learning to Follow Global Paths: Path-Aware RL-based Local Planning
Traditional local navigation relies on waypoint-based planning, where a human provides short-range waypoints (typically 5–30 meters ahead), and the robot navigates to them autonomously. This approach assumes that the waypoints are accurate and reachable. For navigating to distant goals, global planning is typically used to compute a path from satellite data. However, such global paths are coarse, and inaccurate and hence require the robot to intelligently adapt its local behavior to follow them. Simple waypoint tracking tends to break in these situations. One idea to solve this problem is by giving a local planner the full path instead of a look-ahead waypoint, in order to optimize local behavior to take into account the shape of the global path.
Keywords
Reinforcement Learning, Global Navigation, Local Navigation, Rewards, Legged Robots
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Semester Project , Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-08-01
Organization Robotic Systems Lab
Hosts Richter Julia
Topics Information, Computing and Communication Sciences
Gait and Posture Analysis Using Multimodal Data from Smart Walkers
The project aims to develop machine learning models to analyze gait and posture using multimodal data collected from participants using a robotic walker equipped with multiple cameras and inertial sensors. This research focuses on detecting abnormalities in gait patterns and postural control, contributing to the development of rehabilitation and assistive technologies.
Keywords
gait analysis, posture monitoring, smart walker, motion capture, biomechanics, sensor fusion, rehabilitation, inertial sensors
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ETH Zurich (ETHZ)
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Published since: 2025-07-11
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Detection of Cardiovascular Abnormalities from Paper ECG Images Using Deep Learning
This project aims to develop a deep learning algorithm to detect and classify cardiovascular abnormalities directly from paper-based or image-scanned ECGs. By bypassing the need for full digitization, the objective is to enable rapid diagnosis and improve access to cardiovascular healthcare, particularly in resource-limited settings.
Keywords
ECG, cardiovascular disease, image classification, deep learning, global health, medical imaging, underserved populations
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ETH Zurich (ETHZ)
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Published since: 2025-07-11
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Sensorized robot links for distributed contact state estimation
This hardware-focused thesis will build a distributed contact sensing system that can be outfitted to robot links so that it can use information about whole-body contacts with the environment to accomplish new, dynamic tasks.
Keywords
Hardware design, robotics, sensing, tactile sensors, AI, reinforcement learning, humanoids, quadrupeds
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Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-07-14 , Latest end: 2026-05-18
Organization Robotic Systems Lab
Hosts Cramariuc Andrei
Topics Information, Computing and Communication Sciences , Engineering and Technology
Reinforcement Learning for Loco-manipulation
This project aims to develop a reinforcement learning (RL) framework to enable quadruped robots to perform dynamic locomotion and manipulation simultaneously by leveraging advanced RL algorithms . 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.
Keywords
Robotics, quadrupeds, RL, AI,
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Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-07-31 , Latest end: 2026-01-31
Organization Robotic Systems Lab
Hosts Mirrazavi Sina
Topics Information, Computing and Communication Sciences , Engineering and Technology
Enhancing Interlayer Integration and Mechanical Properties in Electrospun and Melt-Electrowritten Scaffolds
This project focuses on improving the mechanical performance and interlayer integration of multiscale scaffolds for articular cartilage tissue engineering. By combining solution electrospinning (SES) and melt electrowriting (MEW), the study aims to fabricate layered fibrous constructs with enhanced structural integrity. A key objective is to explore annealing as a post-processing technique to strengthen the interface between electrospun and MEW layers, addressing a common limitation in scaffold delamination. Morphological and mechanical properties will be assessed through scanning electron microscopy and mechanical testing, with optional biological evaluation using bovine chondrocytes. We are seeking a motivated master's student to contribute to scaffold fabrication, characterization, and cell-based studies within this interdisciplinary research project.
Keywords
Cartilage Tissue engineering Solution Electrospinning Meltelectrowriting Biofabrication Biomaterials
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Semester Project , Internship , Master Thesis
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Published since: 2025-07-10 , Earliest start: 2025-09-01
Organization Tissue Mechanobiology
Hosts Bissacco Elisa
Topics Engineering and Technology
Analog waveform generation for future Point-of-Care Dielectrophoretic devices
This project aims to either simulate or control an electrical microfabricated 3D pillar array
Keywords
Analog design, EM simulation, DAC, Embedded, Control, Micropillar, Field simulation
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-10
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Organization Digital Circuits and Systems (Benini)
Hosts Villani Federico
Topics Engineering and Technology
Internships (Industrial or Research) on Body Modelling and Sensing Technology for Health Care in SCI
This hands-on work (internship or semester project) within a clinical setting will bring you close to intelligent health management while exploring multiple data systems. You will experience multimodal data of robotics rehabilitation, general clinical practice, and detailed clinical studies applied in classification and dimensionality reduction.
Keywords
Machine learning, time-series, HR, ECG, BP, wearables, nearables, Medical and health science, healthcare, Android studio, App development
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Semester Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , Other specific labels , ETH Zurich (ETHZ)
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Published since: 2025-07-10 , Earliest start: 2025-09-01 , Latest end: 2026-06-30
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa , Eawag , Zurich University of the Arts , Zurich University of Applied Sciences , Wyss Translational Center Zurich , University of Zurich , University of St. Gallen , University of Lucerne , University of Lausanne , University of Geneva , University of Fribourg , University of Berne , University of Basel , Lucerne University of Applied Sciences and Arts , Institute for Research in Biomedicine , IBM Research Zurich Lab , Swiss Institute of Bioinformatics , CSEM - Centre Suisse d'Electronique et Microtechnique , Corporates Switzerland , CERN , Hochschulmedizin Zürich , Université de Neuchâtel , Università della Svizzera italiana , Swiss National Science Foundation , University of Konstanz , University of Hamburg , University of Erlangen-Nuremberg , University of Cologne , Universität zu Lübeck , Universität Ulm , Universität der Bundeswehr München , TU Dresden , TU Darmstadt , TU Berlin , Technische Universität Hamburg , Max Planck Society , Otto Von Guericke Universitat, Magdeburg , RWTH Aachen University , Ludwig Maximilians Universiy Munich , Humboldt-Universität zu Berlin , European Molecular Biology Laboratory (EMBL) , Eberhard Karls Universität Tübingen , Max Delbruck Center for Molecular Medicine (MDC) , Technische Universität München , Imperial College London , National Institute for Medical Research , Royal College of Art , UCL - University College London , University of Aberdeen , University of Cambridge , University of Manchester , University of Nottingham , University of Oxford , University of Leeds , Delft University of Technology , Maastricht Science Programme , Radboud University Nijmegen , Utrecht University
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 , Engineering and Technology
Learning-based Traversability Estimation from Experience
Traversability estimation is a critical component in path planning and navigation for mobile robots, especially for legged platforms like quadrupeds that can navigate diverse terrains. Traditionally, traversability estimation relies on data from onboard sensors such as RGB or stereo cameras. However, this approach limits the robot's awareness to its immediate surroundings. By utilizing satellite imagery, we can extend the robot's perception and perform long-range traversability estimation, enabling more efficient global path planning and exploration.
Keywords
Learning-based, Traversability, Navigation, Deep Learning, Legged Robots
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Semester Project , Master Thesis
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Published since: 2025-07-10 , Earliest start: 2025-08-01 , Latest end: 2026-04-30
Organization Robotic Systems Lab
Hosts Cramariuc Andrei , Richter Julia
Topics Information, Computing and Communication Sciences
Neurolink-like brain machine interface in Virtual Reality
https://loaloaf.github.io/VRprojectETH/ We offer a master thesis or research assistant position to study brain-wide neural population dynamics during learning and generalization in rats, using a 1024-channel brain-machine interface in a virtual reality task. Candidates may focus on behavioral experiments—training and handling animals, performing chronic recordings (LTK certificate required)—or on computational analysis of large-scale neural data. Leveraging ultra-flexible electrodes enabling stable, months-long single-unit recordings across 12+ brain regions, the project examines how neural activity reorganizes within low-dimensional manifolds during learning. A central goal is to identify features of neural geometry that reflect evolving behavioral strategies and differentiate plasticity across cortical and subcortical areas.
Keywords
neural population dynamics, brain-machine interface, BMI, BCI, virtual reality learning, systems neuroscience, chronic electrode recordings, flexible electrodes, neural manifolds, behavioral neuroscience, reversal learning, electrophysiology, hippocampus, medial prefrontal cortex, neural coding, animal training, LTK certificate, Python, machine learning, AI, neural data analysis, dimensionality reduction, cognitive flexibility, ETH Zurich
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Semester Project , Internship , Bachelor Thesis , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-07-10 , Earliest start: 2025-07-11 , Latest end: 2025-10-01
Organization Neurotechnology
Hosts Steffens Simon
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Optimization of Electrospinning and Melt-Electrowriting Parameters with a new triblock copolymer
Osteoarthritis (OA), the most prevalent musculoskeletal disorder, leads to degeneration of synovial joints, including articular cartilage. While solution electrospinning (SES) and melt electrowriting (MEW) of poly(ε-caprolactone) (PCL) have shown promise for fabricating fibrous scaffolds for cartilage repair, PCL's low elasticity and slow degradation hinder clinical translation. This project explores a new triblock copolymer, PLLA-b-PCL-b-PLLA, to overcome these limitations. The research aims to optimize SES and MEW parameters and enhance mechanical integrity through annealing of multiscale scaffolds. Scaffold morphology and mechanics will be assessed via SEM and mechanical testing, while biological performance will be evaluated using bovine chondrocytes. The project offers a master's student the opportunity to contribute to the development of improved biomimetic scaffolds for cartilage regeneration.
Keywords
Cartilage Tissue Engineering Solution Electrospinning Meltelectrowriting Biomaterials Biofabrication
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Semester Project , Internship , Master Thesis
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Published since: 2025-07-10 , Earliest start: 2025-09-01
Organization Tissue Mechanobiology
Hosts Bissacco Elisa
Topics Engineering and Technology
Quadruped Glider Feasibility Study
Nature offers elegant examples of energy-efficient aerial locomotion through gliding animals such as flying squirrels and sugar gliders. Inspired by these creatures, this project explores the feasibility of a quadruped robot capable of transitioning from (wheeled-)legged locomotion to gliding flight. This study focuses on a practical first step: mounting a deployable wing on top of a quadruped robot, such as the Unitree Go2. The robot would walk or climb to an elevated launch point, deploy its glider, and perform a controlled passive glide. This opens the door for future hybrid locomotion platforms capable of efficiently navigating both rough ground and long aerial descents. The student(s) will evaluate aerodynamic feasibility through glider performance modeling (e.g., glide ratio, sink rate, stall speed), simulate integration with a quadruped platform, and explore deployment and stability challenges. If viable, preliminary hardware evaluations using off-the-shelf components could be considered. The project also leaves room for long-term vision: future iterations may investigate more integrated, bioinspired control surfaces, should the base platform prove successful, such as membranes between limbs. When done as a two-person project, one student can focus on flight dynamics and aerodynamic simulation, while the other focuses on mechanical integration and physical feasibility. The long-term goal is to assess whether a high-fidelity real-world prototype could be achievable and valuable in robotic exploration or rescue operations.
Keywords
Quadruped Locomotion, Fixed-Wing Flight, Bioinspired Robotics, Passive Gliding, Deployable Wings, Hybrid Mobility, Simulation, Robot Design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-10
Organization Robotic Systems Lab
Hosts Fischer Oliver , Klemm Victor , Rohr David
Topics Information, Computing and Communication Sciences , Engineering and Technology
Perceptive Bipedal‑Wheeled Locomotion Using Direct Depth‑Camera Inputs
Recent work [1] trains perceptive quadrupedal locomotion policies directly from depth images using teacher‑student distillation and RL fine‑tuning, achieving robust traversal over challenging terrain. The egocentric vision problem usually requires RL fine-tuning or more complex training schemes to enable active perception due to the information gap between teacher and student observations. This project aims to bring depth camera-based perceptive locomotion policies to a wheeled-bipedal robot. We believe that this might be more adequate than elevation map-based perception, due to the highly dynamic nature of its locomotion. We put high emphasis on novel training schemes to reduce the number of training phases. Initial inspiration could be drawn from [2]. References: [1]: https://arxiv.org/abs/2505.11164 [2]: https://arxiv.org/abs/2412.09149
Keywords
Perceptive locomotion · Depth camera · Bipedal‑wheeled Robot · End‑to‑end RL · Sim‑to‑real
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Published since: 2025-07-09
Organization Robotic Systems Lab
Hosts Schwarke Clemens , Klemm Victor
Topics Information, Computing and Communication Sciences , Engineering and Technology
Machine Learning Based Estimation of Blood Pressure via Pulse Transit Time and Vascular Dynamics from piezoelectric sensors
This project explores the development and validation of an AI based system for non-invasive blood pressure estimation. The method focuses on deriving pulse transit time (PTT) using dual A-mode piezoelectric sensors (ultrasound) and characterizing vascular features such as arterial wall diameter and flow velocity. The work contributes toward a future wearable ultrasound-based solution for continuous cardiovascular monitoring.
Keywords
machine learning, deep learning, artificial intelligence, blood pressure, pulse transit time, vascular imaging, Doppler
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Published since: 2025-07-09 , Earliest start: 2025-09-01 , Latest end: 2026-08-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Artificial intelligence for anxiety level classification using data from wearable devices
The aim of this project is to study the feasibility of using wearable devices for anxiety detection using machine learning models. By creating a robust framework for continuous monitoring and early assessment, it has the potential to meaningfully impact the users wellbeing.
Keywords
wearable technology, anxiety monitoring, health tracking, machine learning, artificial intelligence
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Published since: 2025-07-09 , Earliest start: 2025-08-01 , Latest end: 2026-06-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Machine learning for Motion Estimation and Fatigue Monitoring Using Triboelectric Nanogenerators
This project explores the feasibility of using triboelectric nanogenerators (TENGs) for joint angle analysis and fatigue monitoring during repetitive human movements using machine learning and deep learning.
Keywords
machine learning, artificial intelligence, generative AI, triboelectric nanogenerator, joint angle estimation, motion analysis, fatigue detection
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Published since: 2025-07-09 , Earliest start: 2025-09-01 , Latest end: 2026-08-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Activity and fatigue detection using machine learning based on real-world data from smart clothing
The aim of this project is to use machine learning methods to extract useful information such as activity type and fatigue level from real-world data acquired from our textile-based wearable technology during sport activities.
Keywords
smart clothing, wearable technology, textile sensor, fitness tracking, sports medicine, fatigue, machine learning, artificial intelligence, computer science
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Published since: 2025-07-09 , Earliest start: 2025-07-01 , Latest end: 2026-03-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Ahmadizadeh Chakaveh
Topics Information, Computing and Communication Sciences , Engineering and Technology
Design data acquisition solution for smart clothing
The aim of this project is to develop and improve wearable electronics solutions for data acquisition from textile-based sensors used in our smart clothing.
Keywords
smart clothing, wearable technology, textile sensor, fitness tracking, sports medicine, PCB, electronics, computer science
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Published since: 2025-07-09 , Earliest start: 2025-07-01 , Latest end: 2025-12-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Ahmadizadeh Chakaveh
Topics Information, Computing and Communication Sciences , Engineering and Technology
Learning Continuous-Time Feedback Laws for Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (HRL) typically operates by decomposing tasks into high-level planners and low-level controllers. While high-level policies often evolve at discrete timescales, the low-level controller must generate fast, robust behaviors. This is usually framed as feedback laws or motion trajectories. In this project, we propose to learn continuous-time dynamical systems in the form of ODEs as low-level feedback controllers. The idea is to learn an ordinary differential equation (ODE) whose integral curve realizes the low-level trajectory, or whose vector field provides feedback behavior. These models offer several advantages: they are interpretable, temporally coherent, and can generalize better under time perturbations. The student will implement and evaluate ODE-based controllers within a hierarchical RL setup and compare their performance against standard low-level policy architectures (e.g., feedforward MLPs, recurrent policies). We are also open to shape the projects in the context of operator learning. References as inspiration: https://arxiv.org/pdf/1806.07366 https://arxiv.org/pdf/1909.12077 https://arxiv.org/pdf/2006.04439 https://arxiv.org/pdf/2402.15715
Keywords
Reinforcement Learning, Neural ODEs, Feedback Control, Hierarchical Policies, Continuous-Time Policies, Operator Learning
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Published since: 2025-07-07
Organization Robotic Systems Lab
Hosts Klemm Victor
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Rigid Body Dynamics as Sum of Squares: Reformulation and Investigation with Optimality Certificates
Rigid-body dynamics are foundational to robotics and mechanical systems. Surprisingly, although their equations often contain trigonometric or rational terms, they can typically be reformulated as (rational) polynomial systems. This opens the door to a powerful toolset: Sum-of-Squares (SOS) optimization. In this project, the student will explore how to reformulate the equations of rigid-body systems into polynomial forms suitable for SOS-based analysis (or its dual, the moment hierarchy). Through this lens, many classic robotics problems, such as verifying the global stability of visuomotor controller [1] or certifying optimality of solutions [2], can be recast as (convex) optimization problems. This project will investigate how far these methods scale: Can we extend them to complex robots? Can we prove properties like exponential stability or generate globally valid Lyapunov functions for general mechanical systems? Can we extract optimality certificates for complex dynamic trajectories? The student will implement tools for converting rigid-body models (e.g., simple pendulums, planar robots) into their polynomial equivalents, and then apply SOS programming and S-procedure techniques to verify Lyapunov stability or derive optimal controllers. References: [1] G. Chou and R. Tedrake, “Synthesizing Stable Reduced-Order Visuomotor Policies for Nonlinear Systems via Sums-of-Squares Optimization,” in IEEE Conference on Decision and Control (CDC), 2023. doi: 10.48550/arXiv.2304.12405. [2] S. Teng, A. Jasour, R. Vasudevan, and M. Jadidi, “Convex Geometric Motion Planning on Lie Groups via Moment Relaxation,” in Robotics: Science and Systems XIX, 2023. doi: 10.15607/RSS.2023.XIX.058.
Keywords
Rigid-Body Dynamics, Polynomial Systems, SOS Optimization, Lyapunov Stability, Convex Programming
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Published since: 2025-07-07
Organization Robotic Systems Lab
Hosts Klemm Victor
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Wearable device for non-invasive assessment of fatigue
The goal of the project is to develop a wearable device capable of non-invasive measurement of human biomarkers related to performance and fatigue during exercise.
Keywords
wearable, fatigue, exercise, sensor, athlete, non-invasive, sport
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Master Thesis
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Published since: 2025-07-07 , Earliest start: 2024-09-01 , Latest end: 2025-09-30
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
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: 2025-07-07 , Earliest start: 2025-09-01 , 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
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: 2025-07-07 , 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
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: 2025-07-07 , 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
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: 2025-07-07 , 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
Wearable 2D Capacitive Auxetic Structures for Motion Monitoring
The aim of this project is to develop a single sensor capable of measuring both unidirectional strain and bending angle.
Keywords
wearable, flexible electronics, 3D printing, capacitive strain sensors
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-06 , Earliest start: 2025-08-01 , Latest end: 2026-12-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Kateb Pierre
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 , Master Thesis
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Published since: 2025-07-06 , Earliest start: 2025-03-24 , Latest end: 2026-08-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Kateb Pierre
Topics Engineering and Technology
Further development of a (gamified) finger training software for a clinical setting
Interessted in designing your own game for patients to train their finger function? Apply to this project:) Finger individuation (the ability to only move one finger independent of the others) is essential for hand function but often impaired after stroke or brain injury. A validated device exists for clinical assessment, including a basic gamified task but for training, more is needed. This project aims to expand finger rehabilitation by developing a training software with engaging exercise games. Based on clinical requirements, you will design, code, and implement motivating training games and excercises into a simple user interface to support finger rehabilitation in clinical settings.
Keywords
Game design, user-centered design, rehabilitation excercise, finger traning
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Published since: 2025-07-04 , Earliest start: 2025-08-04 , Latest end: 2025-12-19
Organization Rehabilitation Engineering Lab
Hosts Knill Anna
Topics Information, Computing and Communication Sciences , Engineering and Technology
Real-Time Delay-Adaptive RL Policy for Autonomous Excavation
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 an RL digging policy that adapts to large and continuously changing time delays. You will conduct your project at Gravis with joint supervision with RSL.
Keywords
Reinforcement Learning Sim2Real
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Semester Project , Master Thesis
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Published since: 2025-07-04 , Earliest start: 2025-09-01 , Latest end: 2026-09-01
Organization Robotic Systems Lab
Hosts Egli Pascal Arturo
Topics Engineering and Technology
Depth Estimation with Event-Based Cameras on nano-UAVs
develop a neural network for depth estimation on nano-drones, using miniaturized event-based cameras, for autonomous navigation
Keywords
nano-drones, robotics, autonomous navigation, depth-estimation, event-based cameras, neuromorphic, neuromorphic vision, embedded systems, tinyML, artificial intelligence, deep learning.
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-04 , Earliest start: 2025-02-03 , Latest end: 2025-12-31
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Engineering and Technology
Digital HW design: accelerator for Event-Based Convolutional Neural Network
Digital HW design: accelerator for Event-Based Convolutional Neural Network
Keywords
Digital HW design, PULP, RISC-V
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-04 , Earliest start: 2025-02-03 , Latest end: 2025-07-31
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Engineering and Technology
Autonomous nano-drone racing
Develop a visual-based neural network for autonomous nano-drone racing, which includes a CNN for gate corners detection, and in-field racing experiments
Keywords
nano-drones, robotics, autonomous navigation, embedded systems,artificial intellicence, deep learning, microcontrollers
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-04 , Latest end: 2026-06-30
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Engineering and Technology
Humanoid robot ladder climbing via learning from demonstrations
This thesis will employ learning from demonstration to enable a humanoid robot to climb ladders. The student will gain hands-on experience with cutting-edge machine learning, sim2real pipelines, and humanoid robot hardware.
Keywords
Humanoids, learning from demonstrations, imitation learning, reinforcement learning, simulation, legged robotics, control, robot, sim2real
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Master Thesis
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Published since: 2025-07-03 , Earliest start: 2025-07-21 , Latest end: 2026-05-01
Organization Robotic Systems Lab
Hosts Li Chenhao , Baines Robert , Hansson Alexander
Topics Information, Computing and Communication Sciences , Engineering and Technology
Learning Acrobatic Excavator Maneuvers
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 an algorithm that allows a 25-ton excavator to perform an acrobatics maneuver, the jump turn.
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Published since: 2025-07-02 , Earliest start: 2025-08-01 , Latest end: 2025-12-01
Organization Robotic Systems Lab
Hosts Egli Pascal Arturo , Zhang Weixuan , Eyschen Pol
Topics Engineering and Technology
Artificial intelligence and perception on insect sized robots
Maze escape with tiny AI-based autonomous bugs
Keywords
Insect-sized robots, robotics, artificial intelligence, embedded systems, autonomous navigation
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Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-07-02 , Earliest start: 2025-07-01
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Engineering and Technology
Visual Object Reconstruction and Generalized Collision-aware Manipulation using Reinforcement Learning
We propose to develop a neural motion planning method that incorporates 3D-reconstructed geometry of in-hand objects into a reinforcement learning policy for collision-aware manipulation. This enables generalization across novel tools and objects with precise, geometry-driven motion in both stationary and mobile robotic setups.
Keywords
Neural motion planning, 3D reconstruction, reinforcement learning, mobile manipulation
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-06-30 , Earliest start: 2025-08-31 , Latest end: 2026-07-31
Organization Robotic Systems Lab
Hosts Portela Tifanny , Zurbrügg René
Topics Information, Computing and Communication Sciences
Master Thesis: Adaptive Motivational Treadmill - Personalized Biofeedback and Avatar-Guided Gait Training
This Master’s thesis project focuses on enhancing gait rehabilitation by integrating real-time heart rate and respiratory monitoring, intelligent treadmill control, and AI-driven avatar feedback. Physiological data are processed by a LLM to generate personalized verbal encouragement, while an AI-based controller adjusts treadmill speed to maintain clinician-defined heart rate zones and adapt to patient performance. The project aims to deliver personalized, engaging, and adaptive rehabilitation and involves system integration, algorithm development, and experimental validation.
Keywords
rehabilitation, robotics, model-based control, LLM integration
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-06-26 , Earliest start: 2025-08-01 , Latest end: 2026-03-31
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Paez Diego, Dr.
Topics Medical and Health Sciences , Engineering and Technology
Development of Wireless Ion Sensing Platforms using Metamaterials and Soft Biointerfaces
This project explores the design and realization of a flexible, wireless ion-sensing patch by integrating resonant metamaterial structures with bio-interfacing soft materials. The system is intended for noninvasive detection of physiologically relevant ions from skin-interfaced fluids using passive sensing mechanisms
Keywords
flexible electronics, metamaterials, wireless biosensors, resonant sensors, skin-compatible interfaces
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-06-26 , Earliest start: 2025-08-01 , Latest end: 2026-01-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Zada Muhammad
Topics Engineering and Technology
3D reconstruction with open-vocabulary reconstruction priors
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 backend regularization techniques.
Keywords
Structure from Motion Visual SLAM
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-06-26 , Earliest start: 2025-07-01
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Learning Manipulation beyond Single End-Effector
Robots, like humans, should be able to use different parts of their morphology (base, elbow, hips, feet) for interaction. This project focuses on learning multi-modal interactions from demonstrations for mobile manipulators.
Keywords
machine learning, manipulation, robotics
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Semester Project , Master Thesis
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Published since: 2025-06-25 , Earliest start: 2024-01-08
Organization Robotic Systems Lab
Hosts Mittal Mayank
Topics Information, Computing and Communication Sciences , Behavioural and Cognitive Sciences
CI/CD Automation and Testing for Embedded Systems
Design and implement a robust CI/CD pipeline for our embedded software development.
Keywords
firmware, embedded, github, cicd, workflow
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Published since: 2025-06-23
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Information, Computing and Communication Sciences
Flash Storage and USB Communication for Embedded Systems
This project targets performance and feature enhancements to a firmware module that manages data transfers from flash memory to a host PC over USB (CDC/ACM). The goal is to improve system reliability, throughput, and communication efficiency for data logging or diagnostic use cases.
Keywords
embedded, c programming, firmware, flash memory, usb
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Published since: 2025-06-23
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Information, Computing and Communication Sciences , Engineering and Technology
Doxygen Documentation Pipeline for Embedded Firmware
You will help improve the usability and maintainability of Skaaltec’s embedded firmware codebase by integrating automated documentation generation using Doxygen.
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Published since: 2025-06-23
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Information, Computing and Communication Sciences
Measurement of hip internal rotation range of motion in individuals with hip joint disorders
Together with the Schulthess Clinic, we have developed the mHIRex which, based on the common clinical manoeuvre, precisely determines the force required for internal hip rotation. The next step is to assess hip internal rotation in a large cohort of patients with hip disorders.
Keywords
hip osteoarthritis, femoroacetabular impingement syndrome, clinical examination, biomechanics
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Internship , Master Thesis
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Published since: 2025-06-20 , Earliest start: 2025-09-24 , Latest end: 2026-12-31
Applications limited to Department of Health Sciences and Technology , Department of Mechanical and Process Engineering
Organization Sensory-Motor Systems Lab
Hosts Wolf Peter
Topics Medical and Health Sciences , Engineering and Technology
RL Finetuning for Generalized Quadruped Locomotion
This project investigates the potential of reinforcement learning (RL) fine-tuning to develop a single, universal locomotion policy for quadruped robots. Building on prior work in multi-terrain skill synthesis [1], we will probe the limits of generalization by systematically fine-tuning on an ever-expanding set of diverse environments. This incremental approach will test the hypothesis that a controller can learn to robustly navigate a vast range of terrains. As a potential extension, procedural terrain generation may be used to automatically create novel challenges, pushing the boundaries of policy robustness.
Keywords
Reinforcement Learning, Quadruped Locomotion
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Master Thesis
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Published since: 2025-06-17 , Earliest start: 2025-06-15
Organization Robotic Systems Lab
Hosts Schwarke Clemens , He Junzhe
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: 2025-06-17 , Earliest start: 2025-01-27
Organization Robotic Systems Lab
Hosts Mittal Mayank , Schwarke Clemens , Klemm Victor
Topics Information, Computing and Communication Sciences
AI-Driven Push Notifications for Monitoring and Enhancing Adherence in At-Home Neurorehabilitation
Adherence to rehabilitation therapy is crucial for the recovery of hand functionality in stroke and traumatic brain injury (TBI) patients. However, sustaining patient motivation to train at home remains a challenge. This project aims to explore the impact of push notifications delivered via LLM chatbots on adherence to physical therapy among stroke and TBI patients. By investigating the optimal frequency and content of notifications, the goal is to develop an AI-driven notification/reminder system that fosters continuous engagement with the rehabilitation plan, ultimately promoting increased therapy and better functional outcomes for patients.
Keywords
App Development, Stroke, Traumatic Brain Injury, Rehabilitation, Adherence to Therapy, Push Notifications, mHealth Apps, Large Language Models, Interdisciplinary Research, React Native
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Published since: 2025-06-17 , Earliest start: 2025-06-22 , Latest end: 2026-09-01
Organization Rehabilitation Engineering Lab
Hosts Retevoi Alexandra
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Learning a Simulation-Trained Safety Critic for Safe Online Learning in Legged Robots
This project focuses on developing a safety critic—a model that predicts the safety of robot states—to enable safe online learning on legged robotic hardware. The safety critic is trained in simulation using labeled data from diverse robot behaviors, identifying states likely to lead to failure (e.g., falls). Once trained, the critic is deployed alongside a learning policy to restrict unsafe exploration, either by filtering dangerous actions or shaping the reward function. The goal is to allow adaptive behavior on real hardware while minimizing physical risk.
Keywords
safety critic, online learning
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Master Thesis
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Published since: 2025-06-16
Organization Robotic Systems Lab
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Engineering and Technology
Data Driven Simulation for End-to-End Navigation
Investigate how neural rendering can become the backbone of comprehensive, next generation data-driven simulation
Keywords
Neural rendering, Simulation
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Internship , Master Thesis
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Published since: 2025-06-16 , Earliest start: 2025-01-27
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Information, Computing and Communication Sciences , 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: 2025-06-16 , 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: 2025-06-16 , Earliest start: 2025-03-17
Organization Robotic Systems Lab
Hosts Kneip Laurent
Topics Engineering and Technology
Personalized Low Latency Interactive AI Project
We are seeking one highly motivated student to join our innovative project focused on developing a cutting-edge voice recognition and personalization platform for wheelchair users This project aims to deliver low-latency, context-aware, and personalized AI interactions in noisy, multi-user environments, leveraging advanced models and distilled LLMs, combined with biosignal tracking and GDPR-compliant data management.
Keywords
Voice recognition, AI personalization, low latency, LLMs, biosignal tracking, neurofeedback, multi-user environments, audio processing
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Semester Project , Internship , Master Thesis
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Published since: 2025-06-11 , Earliest start: 2025-08-01
Organization Sensory-Motor Systems Lab
Hosts Paez Diego, Dr.
Topics Engineering and Technology
Learning to Socially Navigate in Crowds using RL
This project aims to develop a robotic planner that can safely navigate crowded environments, considering human movement patterns and social norms. It seeks to overcome limitations of current planners, which either require privileged information or can't handle semantic constraints. The goal is to create a robust planner for real robots (ANYmal or Unitree B2W) that works in dynamic, constrained environments. Challenges include training an RL policy, expanding movement patterns, and transferring from simulation to real hardware.
Keywords
Reinforcement Learning, Navigation, Planning, Robotics, Legged Robotics, Simulation
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Master Thesis
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Published since: 2025-06-11
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Robotic Systems Lab
Hosts Roth Pascal
Topics Information, Computing and Communication Sciences
Pre-clinical mechanical evaluation of a novel spinal implant
Lower back pain is one of the most prevalent health issues in Switzerland, with severe socio-economic consequences and a leading cause of reduced work performance. Approximately 20% of spinal fusion surgeries performed using off-the-shelf implants result in the surgical outcome being compromised post-operatively, often requiring one or more revision surgeries to address the associated pain. The Laboratory of Orthopedic Technology has recently developed a novel spinal implant using topology optimization, which is currently undergoing a feasibility study for clinical applications. We are seeking a master’s student who is passionate about medical devices and mechanical design and testing to join us for a master thesis. In this role, you will gain insight into the spinal surgery process, receive input from surgeons, and contribute to the mechanical testing of the implant on human cadaveric spine. Objectives: • Perform the CT scan on human cadaveric vertebrae • Evaluate the influence of implant placement/location variability • Mechanical testing on the implant and failure mode analysis • Develop surgical tools if needed • Write related SOPs and testing report Your Profile: • Hands-on and detail-oriented, need to work with human cadaveric bones. • Experience with SolidWorks or Fusion 360, as well as Python or Matlab. • Need to have Hepatitis B Vaccine to be able to work in BSL 2 level labs
Keywords
implant, medical device, mechanical testing, clinical application
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Master Thesis
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Published since: 2025-06-10 , Earliest start: 2025-06-23 , Latest end: 2026-01-30
Organization Bone Pathologies and Treatment
Hosts Du Xiaoyu
Topics Medical and Health Sciences
Active System Identification for Efficient Online Adaptation
This project proposes a novel single-stage training framework for system identification in legged locomotion, addressing limitations in the conventional two-stage teacher-student paradigm. Traditionally, a privileged teacher policy is first trained with full information, followed by a student policy that learns to mimic the teacher using only state-action histories—resulting in suboptimal exploration and limited adaptability. In contrast, our method directly trains a policy to regress privileged information embeddings from its history while simultaneously optimizing for an active exploration objective. This objective is based on maximizing mutual information between the policy’s state-action trajectories and the privileged latent variables, encouraging exploration of diverse dynamics and enhancing online adaptability. The approach is expected to improve sample efficiency and robustness in deployment environments with variable dynamics.
Keywords
Active Exploration, System Identification, Online Adaptation
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Master Thesis
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Published since: 2025-06-06
Organization Robotic Systems Lab
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Engineering and Technology
Learning from Online Demonstrations via Video Diffusion for Local Navigation
This project introduces a framework for local navigation skill acquisition through online learning from demonstrations, bypassing the need for offline expert trajectories. Instead of relying on pre-collected data, we use video diffusion models conditioned on semantic text prompts to generate synthetic demonstration videos in real time. These generated sequences serve as reference behaviors, and the agent learns to imitate them via an image-space reward function. The navigation policy is built atop a low-level locomotion controller and targets deployment on legged platforms such as humanoids and quadrupeds. This approach enables semantically guided, vision-based navigation learning with minimal human supervision and strong generalization to diverse environments.
Keywords
Learning from Demonstrations, Video Diffusion, Semantic Conditioning
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Master Thesis
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Published since: 2025-06-06
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Information, Computing and Communication Sciences
Learning World Models for Legged Locomotion (Structured legged world model)
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: 2025-06-06
Organization Robotic Systems Lab
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
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: 2025-06-05 , Earliest start: 2025-06-01 , Latest end: 2026-04-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Engineering and Technology , Chemistry
How to Touch: Exploring Tactile Representations for Reinforcement Learning
Developing and benchmarking tactile representations for dexterous manipulation tasks using reinforcement learning.
Keywords
Reinforcement Learning, Dexterous Manipulation, Tactile Sensing
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Published since: 2025-06-04 , Earliest start: 2024-12-15 , Latest end: 2025-06-01
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Bhardwaj Arjun , Zurbrügg René
Topics Information, Computing and Communication Sciences
AI-Driven Rock Reshaping Simulation and Control
This project develops an intelligent system for controlling rock fracture by combining finite element analysis (FEM) with machine learning. FEM simulations train a graph neural network (GNN) to predict fracture patterns. A reinforcement learning (RL) agent then uses this predictive GNN to learn optimal actions for guiding fractures towards a desired rock geometry, enabling precise and goal-oriented control.
Keywords
machine learning, deep learning, reinforcement learning, graph neural networks, construction robotics, space robotics
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Published since: 2025-06-02 , Earliest start: 2025-07-07
Organization Robotic Systems Lab
Hosts Spinelli Filippo
Topics Information, Computing and Communication Sciences , Engineering and Technology
Bridging the Gap: Enabling Soft Actor-Critic for High-Performance Legged Locomotion
Proximal Policy Optimization (PPO) has become the de facto standard for training legged robots, thanks to its robustness and scalability in massively parallel simulation environments like IsaacLab. However, alternative algorithms such as Soft Actor-Critic (SAC), while sample-efficient and theoretically appealing due to entropy maximization, have not matched PPO’s empirical success in this domain. This project aims to close that performance gap by developing and evaluating modifications to SAC that improve its stability, scalability, and sim-to-real transferability on legged locomotion tasks. We benchmark SAC against PPO using standardized pipelines and deploy learned policies on real-world quadruped hardware, pushing toward more flexible and efficient reinforcement learning solutions for legged robotics.
Keywords
Legged locomotion, Soft Actor-Critic, Reinforcement learning, Sim-to-real transfer
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Master Thesis
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Published since: 2025-05-30
Organization ETH Competence Center - ETH AI Center
Hosts Li Chenhao , Li Chenhao , Li Chenhao , Li Chenhao
Topics Information, Computing and Communication Sciences
Internship or Master Thesis Opportunity in Pupil-Based Biofeedback data analysis
Are you passionate about neuroinformatics, data science, or biosignal processing and looking for an exciting internship/master thesis opportunity at ETH Zurich and SFISM? Join our interdisciplinary team in an SNF BRIDGE project that explores how pupil-based biofeedback training can help athletes to regulate their state of arousal. Arousal regulation is critical for cognitive performance and well-being. Our research focuses on using the pupil as a real-time physiological marker of central arousal, linked to the locus coeruleus-noradrenaline (LC-NA) system. We have developed an innovative pupil-based biofeedback system integrated into commercially available VR headsets with eye-tracking capabilities. Our goal is to investigate how prolonged pupil biofeedback training influences self-regulation of arousal at rest and during cognitive tasks, and how factors such as demographics and personality traits shape its effectiveness. The project will be jointly supervised by the Neural Control of Movement lab at ETH Zurich and the Sports Psychology group at SFISM. A substantial part of the research activities will take place in Magglingen.
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pupillometry, time series analysis, neuroscience, biofeedback, neurofeedback
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Semester Project , Internship , Master Thesis
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Published since: 2025-05-27 , Earliest start: 2025-06-15 , Latest end: 2026-03-01
Organization Neural Control of Movement Lab
Hosts Weijs Marieke
Topics Medical and Health Sciences
Master Thesis - Signal Processing for Neurological Data
We are offering a Masters thesis project for a motivated student to develop a complete signal processing pipeline tailored to neurological data, with the goal of detecting early biomarkers of cognitive or neurological conditions. This project blends neuroscience, signal processing, and artificial intelligence in a practical and high-impact context.
Keywords
signal processing, neurological data, fNIRS, EEG, neuroimaging, brain-computer interface, biomedical signal processing, artifact removal, noise reduction, ICA, wavelet denoising, feature extraction, FFT, PSD, ERP, hemodynamic response, connectivity analysis, machine learning, AI, classification, clustering, SVM, Random Forest, deep learning, PCA, LDA, anomaly detection, biomarkers, neuroscience, Python, MNE, scikit-learn, PyTorch, TensorFlow, Optohive, ETH Zurich, Relab
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-22 , Earliest start: 2025-08-01 , Latest end: 2026-06-01
Organization Rehabilitation Engineering Lab
Hosts Willhaus Marc
Topics Medical and Health Sciences , Engineering and Technology , Biology , Physics
Master Thesis - Deep Learning and AI Modelling of Neurological Data
We are looking for a master student who codevelops AI and machine learning models and inference pipelines on the base of neurological fNIRS sensory data.
Keywords
deep learning, time-series, fNIRS, EEG, EMG, neurotechnology, neurological data, sequence modeling, CNN, LSTM, GRU, Transformer, hybrid models, self-supervised learning, contrastive learning, biomarker discovery, AI, machine learning, brain-computer interface, data augmentation, model interpretability, Grad-CAM, SHAP, saliency maps, biomedical signal processing, PyTorch, TensorFlow, Python, Optohive, ETH Zurich, Relab
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-22 , Earliest start: 2025-07-01 , Latest end: 2026-06-01
Organization Rehabilitation Engineering Lab
Hosts Willhaus Marc
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Physics
Learning Terrain Traversal from Human Strategies for Agile Robotics
Teaching robots to walk on complex and challenging terrains, such as rocky paths, uneven ground, or cluttered environments, remains a fundamental challenge in robotics and autonomous navigation. Traditional approaches rely on handcrafted rules, terrain classification, or reinforcement learning, but they often struggle with generalization to real-world, unstructured environments.
Keywords
3D reconstruction, egocentric video, SMPL representation
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Semester Project , Master Thesis
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Published since: 2025-05-21 , Earliest start: 2025-05-26
Organization Computer Vision and Geometry Group
Hosts Wang Xi , Frey Jonas , Patel Manthan , Kaufmann Manuel , Li Chenhao
Topics Information, Computing and Communication Sciences
HandoverNarrate: Language-Guided Task-Aware Motion Planning for Handovers with Legged Manipulators
This project addresses the challenge of task-oriented human-robot handovers, where a robot must transfer objects in a manner that directly facilitates the human’s next action. In our prior work, we demonstrated that robots can present objects appropriately for immediate human use by leveraging large language models (LLMs) to reason about task context. However, integrating task-specific physical constraints—such as ensuring a full mug remains upright during transport—into the motion planning process remains unsolved. In this project, we aim to extend our existing motion planning framework for legged manipulators by incorporating such constraints. We propose using LLMs to dynamically generate task-aware constraint formulations based on high-level task descriptions and object states. These constraints will then be used to adjust the cost function of the model predictive controller in real time, enabling more context-sensitive and physically appropriate handovers.
Keywords
language-guided motion planning, legged robotics, human-robot collaboration
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Semester Project , Bachelor Thesis
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Published since: 2025-05-21
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Tulbure Andreea
Topics Information, Computing and Communication Sciences
Humanoid Locomotion in Rough Terrain via Imitation Learning
TLDR: Make Humanoid walk in rough terrain using human demonstration and RL
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Semester Project , Master Thesis
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Published since: 2025-05-21 , Earliest start: 2025-05-31 , Latest end: 2025-09-30
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Zurich
Organization Robotic Systems Lab
Hosts Frey Jonas
Topics Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
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: 2025-05-20 , Earliest start: 2025-06-01
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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Collaboration , Master Thesis
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Published since: 2025-05-20 , Earliest start: 2025-06-01
Organization Rehabilitation Engineering Lab
Hosts Domnik Nadine
Topics Medical and Health Sciences , 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: 2025-05-19 , 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
Development and Testing of Electrical Systems for a SmartVNS Docking Station with Focus on Wireless Data Management
We are looking for an enthusiastic electrical/firmware engineer to design and implement the electrical and firmware aspects of a docking station for the SmartVNS device. The station will charge the device components (pulse generator and wrist motion tracker) and pull data from the pulse generator and motion tracker, uploading it to an online server via Wi-Fi. This project will also involve testing the reliability of data transfer and power systems under real-world conditions, providing valuable insights into the practical application of this technology.
Keywords
Electrical, embedded, electronic, engineering, biomedical
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Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-05-19 , Earliest start: 2024-08-18 , Latest end: 2025-10-01
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Information, Computing and Communication Sciences , Engineering and Technology
Development of Regulatory Documentation for a Novel Neurorehabilitation Device: Preparation for FDA and Swissmedic Compliance
Stroke is a leading cause of long-term disability, affecting millions annually and necessitating innovative approaches to rehabilitation. The Rehabilitation Engineering Laboratory (RELab) at ETH Zurich is developing a novel closed-loop neurorehabilitation device that integrates real-time motion tracking with non-invasive brain stimulation to enhance neural plasticity and promote motor recovery in stroke patients. To advance this technology toward clinical trials, comprehensive regulatory documentation is essential to meet the stringent requirements of the U.S. Food and Drug Administration (FDA) and Swissmedic. This project focuses on preparing an Investigational Device Exemption (IDE) application for the FDA and supporting documentation for Swissmedic compliance, including technical descriptions, risk analyses, and clinical study protocols. The student will conduct literature reviews, draft regulatory documents, and support risk management in accordance with ISO 14971, contributing to the device’s regulatory pathway. This work offers a unique opportunity to gain expertise in medical device regulation, bridging biomedical engineering and neuroscience, and advancing a transformative solution for stroke rehabilitation.
Keywords
regulatory affairs, medical device, non-invasive brain stimulation, FDA, Swissmedic, investigational device exemption, IDE, stroke rehabilitation, compliance
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-05-19 , Earliest start: 2025-05-25 , Latest end: 2025-08-01
Organization Rehabilitation Engineering Lab
Hosts Donegan Dane , Viskaitis Paulius
Topics Medical and Health Sciences , Engineering and Technology
Global Optimization Enabled by Learning
We aim to characterize optimization landscapes using metrics such as Sobolev norms, measuring function smoothness, Hessian spectral properties, indicating curvature, and the tightness of semidefinite programming (SDP) relaxations (relevant for polynomial optimization). The core innovation lies in translating these metrics into differentiable objectives or regularizers. By incorporating these into the training process, we encourage the learned modules to produce downstream optimization problems that are inherently well-conditioned and possess favourable global structures
Keywords
Optimization, Learning, Optimal, Robotics
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-19 , Earliest start: 2025-06-01 , Latest end: 2026-06-01
Organization Robotic Systems Lab
Hosts Talbot William , Tuna Turcan
Topics Engineering and Technology
Strategic Financial Modelling and Business Plan Development for a Breakthrough Neurorehabilitation Device
With over 14 million stroke cases annually, the global neurorehabilitation market presents a multi-billion-dollar opportunity for innovative solutions addressing motor recovery. The Rehabilitation Engineering Laboratory (RELab) at ETH Zurich is developing a revolutionary closed-loop neurorehabilitation device that leverages motion tracking and non-invasive brain stimulation to transform stroke rehabilitation. This project aims to develop a sophisticated financial model and a strategic business plan to propel the device to market leadership. The student will conduct market analysis, build financial projections, and craft a compelling business strategy, focusing on pricing, reimbursement, and investor engagement. By delivering investor-ready materials and a scalable commercialization plan, this work will position the device for rapid market entry and long-term success, offering the student a unique opportunity to blend business strategy, entrepreneurship, and healthcare innovation.
Keywords
financial modelling, business strategy, medical device, neurorehabilitation, startup, stroke rehabilitation, entrepreneurship, market entry, investment
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-05-19 , Earliest start: 2025-05-25 , Latest end: 2025-09-01
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Medical and Health Sciences , Engineering and Technology , Economics , Commerce, Management, Tourism and Services
Design and development of a novel printing approach
3D printing has revolutionized the way objects are designed and fabricated across a wide range of industries—from aerospace and automotive to healthcare and consumer products. It enables rapid prototyping, complex geometries, customized solutions, and recently bioprinting of living tissues that are difficult or impossible to achieve with traditional manufacturing methods. Every 3D printing method has certain drawbacks, often related to resolution, material compatibility, speed, or scalability. The ongoing search for new approaches aims to overcome these challenges and expand the potential of the technology. We have developed and demonstrated a proof of concept for a novel printing approach, and are now seeking to advance it into a fully functional prototype.
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Semester Project , Master Thesis
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Published since: 2025-05-15 , Earliest start: 2025-06-01 , Latest end: 2025-12-31
Organization Zenobi-Wong Group / Tissue Engineering and Biofabrication
Hosts Janiak Jakub
Topics Engineering and Technology
Stanford – UC Berkeley Collaboration: Learning Progress Driven Reinforcement Learning for ANYmal
TLDR: Improving navigation capabilities of ANYmal - RL is simulation - optimizing learning progress.
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Semester Project , Master Thesis
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Published since: 2025-05-14 , Earliest start: 2025-05-14 , Latest end: 2025-08-31
Applications limited to EPFL - Ecole Polytechnique Fédérale de Lausanne , ETH Zurich , University of Zurich
Organization Robotic Systems Lab
Hosts Frey Jonas
Topics Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Visual Language Models for Long-Term Planning
This project uses Visual Language Models (VLMs) for high-level planning and supervision in construction tasks, enabling task prioritization, dynamic adaptation, and multi-robot collaboration for excavation and site management. prioritization, dynamic adaptation, and multi-robot collaboration for excavation and site management
Keywords
Visual Language Models, Long-term planning, Robotics
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Semester Project , Master Thesis
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Published since: 2025-05-07 , Earliest start: 2025-06-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
AI Agents for Excavation Planning
Recent advancements in AI, particularly with models like Claude 3.7 Sonnet, have showcased enhanced reasoning capabilities. This project aims to harness such models for excavation planning tasks, drawing parallels from complex automation scenarios in games like Factorio. We will explore the potential of these AI agents to plan and optimize excavation processes, transitioning from simulated environments to real-world applications with our excavator robot.
Keywords
GPT, Large Language Models, Robotics, Deep Learning, Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-05-07 , Earliest start: 2025-07-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Engineering and Technology
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 , Kneip Laurent
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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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
Gaussian Avatar Reconstruction from Single Image
In this project, you are going to work with a state-of-the-art deep learning approach and generative models for building an efficient system to directly reconstruct a 3D animatable avatar from a single image. Feel free to contact me for more details.
Keywords
3D Gaussian Avatar, Diffusion Model, 3D from single image
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-04-23 , Earliest start: 2025-05-01 , Latest end: 2025-12-15
Organization Advanced Interactive Technologies
Hosts Dong Zijian
Topics Information, Computing and Communication Sciences
Tissue Engineering Approaches to Study Tendon Injury, Disease, and Therapy
Join a dynamic research team at the intersection of biomechanics, tissue engineering, and cell biology. This project offers hands-on training in state-of-the-art methods to investigate how tendon tissue responds to injury, disease processes, and mechanical stimulation during exercise-based therapy.
Keywords
Tendon biology, tissue engineering, mechanobiology, cell culture, microscopy, regenerative medicine, exercise therapy, inflammation, ECM remodeling
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Master Thesis
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Published since: 2025-04-15 , Earliest start: 2025-05-01 , Latest end: 2026-12-31
Organization Snedeker Group / Laboratory for Orthopaedic Biomechanics
Hosts Snedeker Jess, Prof.
Topics Engineering and Technology
PCB design for neuromorphic vision on nano-drones
In this project, we aim to develop a novel PCB integrating a powerful PULP chip, i.e., the GAP9, and event-based sensor, the Prophesee Genx320, and a RGB camera, the Himax HB0360 to enable multi modal AI-driven perception aboard nano-drones
Keywords
PCB design, nano-drones, robotics, event-cameras, neuromorphic computing, embedded devices, ultra-low-power
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-04-07 , Earliest start: 2025-04-07 , Latest end: 2025-12-01
Organization Digital Circuits and Systems (Benini)
Hosts Lamberti Lorenzo
Topics Engineering and Technology
Exploring the Mechanoregulation of Bone Regeneration
In over 100 years, the remarkable ability of bone to adapt to its mechanical environment has been a source of scientific fascination. Bone regeneration has been shown to be highly dependent on the mechanical environment at the fracture site. It has been demonstrated that mechanical stimuli can either accelerate or impede regeneration. Despite the fundamental importance of the mechanical environment in influencing bone regeneration, the molecular mechanisms underlying this phenomenon are complex and poorly understood.
Keywords
Bone, Mechanobiology, Spatial transcriptomics, Gene expression, Finite element modelling, Image processing
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-03-23 , Earliest start: 2024-11-01 , Latest end: 2026-08-31
Organization Müller Group / Laboratory for Bone Biomechanics
Hosts Mathavan Neashan
Topics Medical and Health Sciences , 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: 2025-07-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Werner Lennart , Egli Pascal Arturo , Terenzi Lorenzo , Nan Fang , Zhang Weixuan
Topics Information, Computing and Communication Sciences
Exploring the 3D Mineralization Behavior in Material-Induced Osteoinduction Through a Multiscale Micro-CT Imaging Approach
The project aims at investigating material-induced osteoinduction using the available mouse model of orthotopic or ectopic bone graft substitute (BGS) application. Through the 3D-3D registration of ex vivo and in vivo multiscale micro-CT images, crucial 3D mineralization behavior of the BGS can be investigated.
Keywords
Femur, Bone Graft Substitute, Critical Size Defect, Osteoinduction, in vivo, micro-CT, 3D-3D Image Registration, Image Analysis, Image Processing, Python, Computational
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-03-11 , Earliest start: 2025-04-01 , Latest end: 2026-01-31
Organization Müller Group / Laboratory for Bone Biomechanics
Hosts Lindenmann Sara
Topics Medical and Health 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
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