Semester Project

Semester Projects at IRIS

ETH Zurich uses SiROP to publish and search scientific projects. For more information visit sirop.org.

Wearable 2D Capacitive Auxetic Structures for Motion Monitoring

Biomedical and Mobile Health Technology Lab

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: 2025-06-24 , 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

Biomedical and Mobile Health Technology Lab

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: 2025-06-18 , Earliest start: 2025-03-24 , Latest end: 2026-08-31

Organization Biomedical and Mobile Health Technology Lab

Hosts Kateb Pierre

Topics Engineering and Technology

Differentiable Simulation for Precise End-Effector Tracking

Robotic Systems Lab

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

Rehabilitation Engineering Lab

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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Semester Project , Bachelor Thesis , Master Thesis

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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

AI-Based Motion Estimation and Fatigue Monitoring Using Triboelectric Nanogenerators

Biomedical and Mobile Health Technology Lab

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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Semester Project , Master Thesis

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Published since: 2025-06-16 , Earliest start: 2025-07-01 , Latest end: 2026-06-30

Organization Biomedical and Mobile Health Technology Lab

Hosts Otesteanu Corin, Dr

Topics Information, Computing and Communication Sciences , Engineering and Technology

Utilizing the human body for ambient electromagnetic energy harvesting

Biomedical and Mobile Health Technology Lab

The goal of the project is to develop wearable devices, for use in environmental electromagnetic energy recovery based on human body application.

Keywords

Flexible electronics, electromagnetic energy harvesting

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Semester Project , Bachelor Thesis , Master Thesis

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Published since: 2025-06-15 , Earliest start: 2025-06-20

Organization Biomedical and Mobile Health Technology Lab

Hosts Li Yuanlong

Topics Engineering and Technology

AI-Based Estimation of Blood Pressure via Pulse Transit Time and Vascular Dynamics from piezoelectric sensors

Biomedical and Mobile Health Technology Lab

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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Semester Project , Master Thesis

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Published since: 2025-06-12 , Earliest start: 2025-06-30 , Latest end: 2026-06-30

Organization Biomedical and Mobile Health Technology Lab

Hosts Otesteanu Corin, Dr

Topics Information, Computing and Communication Sciences , Engineering and Technology

Activity and fatigue detection using machine learning based on real-world data from smart clothing

Biomedical and Mobile Health Technology Lab

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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Semester Project , Bachelor Thesis , Master Thesis

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Published since: 2025-06-12 , 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

Biomedical and Mobile Health Technology Lab

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: 2025-06-12 , 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

Reinforcement Learning for Drone Maneuvers from Human Preferences

Robotics and Perception

Learn complex drone maneuvers from human feedback using Reinforcement Learning (RL).

Keywords

Reinforcement Learning from human feedback (RLHF), Drones, Robotics

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Semester Project , Master Thesis

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Published since: 2025-06-12 , Earliest start: 2024-05-15 , Latest end: 2026-04-01

Organization Robotics and Perception

Hosts Geles Ismail

Topics Information, Computing and Communication Sciences , Engineering and Technology

Personalized Low Latency Interactive AI Project

Sensory-Motor Systems Lab

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

How to Touch: Exploring Tactile Representations for Reinforcement Learning

Robotic Systems Lab

Developing and benchmarking tactile representations for dexterous manipulation tasks using reinforcement learning.

Keywords

Reinforcement Learning, Dexterous Manipulation, Tactile Sensing

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Semester Project , Bachelor Thesis , Master Thesis

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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

Robotic Systems Lab

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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Semester Project , Master Thesis

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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

Perceptive Arm Motion Planning and Control for Heavy Construction Machine Tasks

Robotic Systems Lab

In this work we would utilize reinforcement learning, neural network actuator modeling, and perception for the control and arm motion planning of a 40ton excavator with a free-swinging gripper. The project will be in collaboration with Gravis Robotics, ETH spinoff working on the automation of heavy machinery.

Keywords

reinforcement learning, perception, hydraulics, excavator, manipulation, industry

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Semester Project , Collaboration , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-06-02 , Earliest start: 2025-07-07

Organization Robotic Systems Lab

Hosts Egli Pascal Arturo , Terenzi Lorenzo , Spinelli Filippo

Topics Information, Computing and Communication Sciences , Engineering and Technology

Development of Neuromuscular Biohybrid Robots

Soft Robotics Lab

Biohybrid robots integrate living cells and synthetic components to achieve motion. These systems often rely on engineered skeletal muscle tissues that contract upon electrical stimulation for actuation. Neuromuscular-powered biohybrid robots take this concept further by integrating motor neurons to induce muscle contractions, mimicking natural muscle actuation. In our lab, we are developing neuromuscular actuators using advanced 3D co-culture systems and biofabrication techniques to enable functional macro-scale biohybrid robots.

Keywords

Tissue engineering, mechanical engineering, biology, neuroengineering, biomaterials, biohybrid robotics, 3D in vitro models, biofabrication, bioprinting, volumetric printing.

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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-05-28 , Earliest start: 2025-06-02

Organization Soft Robotics Lab

Hosts Badolato Asia , Katzschmann Robert, Prof. Dr.

Topics Medical and Health Sciences , Engineering and Technology , Biology

Learning Terrain Traversal from Human Strategies for Agile Robotics

Computer Vision and Geometry Group

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

Robotic Systems Lab

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

Robotic Systems Lab

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

Embedded algorithms of IMUs in a neurorehabilitation device

Rehabilitation Engineering Lab

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 of Regulatory Documentation for a Novel Neurorehabilitation Device: Preparation for FDA and Swissmedic Compliance

Rehabilitation Engineering Lab

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

Robotic Systems Lab

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

Rehabilitation Engineering Lab

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

Stanford – UC Berkeley Collaboration: Learning Progress Driven Reinforcement Learning for ANYmal

Robotic Systems Lab

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

Fine-tuning Policies in the Real World with Reinforcement Learning

Robotics and Perception

Explore online fine-tuning in the real world of sub-optimal policies.

Keywords

online fine-tuning, reinforcement learning (RL), continual learning, drones, robotics

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Published since: 2025-05-13 , Earliest start: 2025-06-01 , Latest end: 2026-04-30

Organization Robotics and Perception

Hosts Geles Ismail

Topics Information, Computing and Communication Sciences , Engineering and Technology

Inverse Reinforcement Learning from Expert Pilots

Robotics and Perception

Use Inverse Reinforcement Learning (IRL) to learn reward functions from previous expert drone demonstrations.

Keywords

Inverse Reinforcement Learning, Drones, Robotics

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Published since: 2025-05-13 , Earliest start: 2025-06-01 , Latest end: 2026-04-30

Organization Robotics and Perception

Hosts Geles Ismail

Topics Information, Computing and Communication Sciences , Engineering and Technology

Advancing Low-Latency Processing for Event-Based Neural Networks

Robotics and Perception

Design and implement efficient event-based networks to achieve low latency inference.

Keywords

Computer Vision, Event Cameras

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Semester Project , Master Thesis

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Published since: 2025-05-12 , Earliest start: 2024-12-12

Organization Robotics and Perception

Hosts Messikommer Nico

Topics Information, Computing and Communication Sciences

Multi-Critic Reinforcement Learning for Whole-Body Control of Bimanual Legged Manipulator

Robotic Systems Lab

Recent work in legged robotics shows the promise of unified control strategies for whole-body control. Portela et al. (2024) demonstrated force control without force sensors, enabling compliant manipulation through body coordination. In another study, they achieved accurate end-effector tracking using whole-body RL with terrain-aware sampling. Fu et al. (2023) showed that unified policies can dynamically handle both movement and manipulation in quadruped robots by training with two critics: one for arms, and one for legs, and then gradually combining them. In this project, you will investigate reinforcement learning for whole body control of a bimanual legged manipulator. You will implement a baseline single-critic whole body controller for the system. You will then investigate different multi-critic approaches and their effects on the training and final performance of the whole-body controller. References: Learning Force Control for Legged Manipulation, Portela et al., 2024 Whole-Body End-Effector Pose Tracking, Portela et al., 2024 Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion, Fu et al., 2023

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Semester Project , Master Thesis

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Published since: 2025-05-09 , Earliest start: 2025-05-11 , Latest end: 2025-12-31

Applications limited to ETH Zurich , [nothing]

Organization Robotic Systems Lab

Hosts Fischer Oliver , Elanjimattathil Aravind

Topics Engineering and Technology

Visual Language Models for Long-Term Planning

Robotic Systems Lab

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

Robotic Systems Lab

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

Modelling and Optimizing the Power Budget of a Bridge-Mounted Camera System for River Waste Monitoring

Robotic Systems Lab

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

Robotic Systems Lab

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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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

Robotic Systems Lab

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

Robotic Systems Lab

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

Agile Flight of Flexible Drones in Confined Spaces

Robotics and Perception

The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints.

Keywords

Robotics, Autonomous Systems, Model Predictive Control, Quadcopter, Drone Racing, Approximate Dynamic Programming, Model-Based Reinforcement Learning

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Semester Project , Master Thesis

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Published since: 2025-04-17 , Earliest start: 2025-06-01 , Latest end: 2026-03-01

Organization Robotics and Perception

Hosts Reiter Rudolf

Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Vision-Based World Models for Real-Time Robot Control

Robotics and Perception

This project aims to use vision-based world models as a basis for model-based reinforcement learning, aiming to achieve a generalizable approach for drone navigation.

Keywords

Robotics, Autonomous Systems, Computer Vision, Foundation Models, Reinforcement Learning

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Semester Project , Master Thesis

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Published since: 2025-04-17 , Earliest start: 2025-05-01 , Latest end: 2026-02-28

Organization Robotics and Perception

Hosts Reiter Rudolf

Topics Information, Computing and Communication Sciences

Vision-Based Reinforcement Learning in the Real World

Robotics and Perception

We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning.

Keywords

Robotics, Autonomous Systems, Computer Vision, Reinforcement Learning

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Semester Project , Master Thesis

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Published since: 2025-04-17 , Earliest start: 2025-05-01 , Latest end: 2026-02-01

Organization Robotics and Perception

Hosts Reiter Rudolf

Topics Information, Computing and Communication Sciences , Engineering and Technology

Language-guided Drone Control

Robotics and Perception

Explore the use of large vision language models to control a drone.

Keywords

Human-drone interaction, large language models (LLMs), Robotics

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Semester Project , Master Thesis

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Published since: 2025-04-10 , Earliest start: 2025-05-01 , Latest end: 2026-02-28

Organization Robotics and Perception

Hosts Geles Ismail

Topics Information, Computing and Communication Sciences , Engineering and Technology

Smart Microcapsules for Biomedical Advances

Multiscale Robotics Lab

This Master's thesis/semester project focuses on the microfluidic fabrication of microcapsules with multi-environmental responsiveness. The aim is to develop microcapsule-based microrobots capable of adapting to various environmental cues. We envision that these microrobots will be used for complex tasks in biomedical applications.

Keywords

Microfluidics, Microcapsules, Microrobotics, Responsive Polymers, Biomedical Engineering

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Semester Project , Internship , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)

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Published since: 2025-04-08 , Earliest start: 2025-07-01

Organization Multiscale Robotics Lab

Hosts Hu Minghan

Topics Medical and Health Sciences , Engineering and Technology , Chemistry

Low-Voltage Soft Actuators for Developing Untethered Robotic Systems

Soft Robotics Lab

We are building the next generation of HALVE (Hydraulically Amplified Low-Voltage Electrostatic) actuators which are flexible, pouch-based electrostatic actuators that operate at voltages 5–10× lower than traditional soft electrostatic systems. You will help us explore novel actuator geometries, ultra-thin functional layers, and new fabrication techniques to unlock scalable, energy-efficient soft robotic systems.

Keywords

soft robotics, low-voltage actuation, dielectric elastomers, electrostatic actuators, fabrication, PVDF-TrFE-CTFE, vapor deposition, CNC sealing, mechatronics, materials science

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Published since: 2025-04-07 , Earliest start: 2025-04-14 , Latest end: 2026-01-31

Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa

Organization Soft Robotics Lab

Hosts Albayrak Deniz , Hinchet Ronan

Topics Engineering and Technology

Combined Muscle and Nerve Tissue Engineering

Soft Robotics Lab

Engineered muscle tissues have applications in regenerative medicine, drug testing, and understanding motion. A key challenge is restoring neuromuscular communication, especially in treating volumetric muscle loss (VML). This project aims to create functional neuromuscular constructs with biomimetic innervation. Scaffolds will be made using electrospun fibers, conductive materials, and drug-loaded graphene. Muscle and nerve cells derived from iPSCs will be seeded into these scaffolds. Constructs will be tested for motion, drug response, and integration in bio-hybrid robotic systems. The platform will advance muscle-nerve regeneration, drug testing, and bio-hybrid robotics.

Keywords

Tissue engineering, innervation, neural tissue, nerve, muscle tissue, scaffold, iPSCs, muscle cells, bioprinting, biofabrication, biohybrid robotics, soft robotics, 3D printing, biomaterials, electrical stimulation, actuation.

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Published since: 2025-04-06 , Earliest start: 2025-04-06 , Latest end: 2025-09-30

Organization Soft Robotics Lab

Hosts Filippi Miriam

Topics Medical and Health Sciences , Engineering and Technology , Biology

Develop Dexterous Humanoid Robotic Hands

Soft Robotics Lab

Design and build dexterous human-like robotic hands with us at the Soft Robotics Lab and the ETH spin-off mimic. We will explore different possibilities of developing design features and sub-systems. The developed features shall be integrated into a fully functional robotic hand and applied to solve practical manipulation challenges.

Keywords

humanoid, robotics, hand, dexterity, soft robotics, actuation, prototyping, modeling and control, mechatronics, biomimetic, design, 3D printing, silicone casting, electronics, machine learning, control

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Published since: 2025-03-24 , Earliest start: 2025-01-01 , Latest end: 2026-03-31

Organization Soft Robotics Lab

Hosts Weirich Stefan

Topics Engineering and Technology

Time-continuous Facial Motion Capture Using Event Cameras

Robotics and Perception

Traditional facial motion capture systems, including marker-based methods and multi-camera rigs, often struggle to capture fine details such as micro-expressions and subtle wrinkles. While learning-based techniques using monocular RGB images have improved tracking fidelity, their temporal resolution remains limited by conventional camera frame rates. Event-based cameras present a compelling solution, offering superior temporal resolution without the cost and complexity of high-speed RGB cameras. This project explores the potential of event-based cameras to enhance facial motion tracking, enabling the precise capture of subtle facial dynamics over time.

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Published since: 2025-03-19 , Earliest start: 2025-03-23 , Latest end: 2025-12-31

Organization Robotics and Perception

Hosts Pellerito Roberto

Topics Engineering and Technology

Intelligent Micromachines Made from Droplet-Based Factory

Multiscale Robotics Lab

We invite applications for a Master's thesis / semester project that focuses on the fabrication of microrobots with custom shapes. Using our developed droplet printing technique, this project will explore how different microrobot shapes, created by different magnetic fields and materials, influence their control behaviors in blood vessels. This research aims to advance biomedical technologies, particularly in targeted drug delivery and minimally invasive procedures.

Keywords

Microrobotics, 4D Printing, Soft Materials, Biomedical Devices

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Semester Project , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)

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Published since: 2025-03-18 , Earliest start: 2025-06-02

Organization Multiscale Robotics Lab

Hosts Hu Minghan

Topics Engineering and Technology , Chemistry

Better Scaling Laws for Neuromorphic Systems

Robotics and Perception

This project explores and extends the novel "deep state-space models" framework by leveraging their transfer function representations.

Keywords

deep learning, state space models, transfer function, parameterizations, S4 model, Fourier Transform, Convolution, Neuromorphic Systems, Neuromorphic, Sequence Modeling, Event-based Vision

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Published since: 2025-03-18

Applications limited to University of Zurich , ETH Zurich

Organization Robotics and Perception

Hosts Zubic Nikola

Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Generalist Excavator Transformer

Robotic Systems Lab

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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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

Development of intelligent lab-on-a-chip devices for high-throughput cell manipulation and microrobot production

Multiscale Robotics Lab

Microfluidic devices can be employed in biological research as lab-on-a-chip (LoC) and organ-on-a-chip (OoC) systems. These platforms enable precise in-situ cell manipulation within a highly controlled environment. In the project, we aim to develop an intelligent LoC/OoC device featuring a flexible smart “switch”, for massive production of biohybrid microrobots and high-throughput cell manipulation and drug testing.

Keywords

Lab-on-a-chip, organ-on-a-chip, magnetic microrobot, cell manipulation

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Published since: 2025-03-05 , Earliest start: 2025-03-10 , Latest end: 2025-12-31

Applications limited to ETH Zurich , Empa , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Basel , University of Berne , University of Fribourg , University of Geneva , University of Lausanne , University of Lucerne , University of St. Gallen , University of Zurich , Zurich University of Applied Sciences , Zurich University of the Arts , Hochschulmedizin Zürich , Lucerne University of Applied Sciences and Arts

Organization Multiscale Robotics Lab

Hosts Zhu Jiawei

Topics Engineering and Technology , Biology

Beyond Value Functions: Stable Robot Learning with Monte-Carlo GRPO

Robotic Systems Lab

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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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

Deep Learning of Residual Physics For Soft Robot Simulation

Soft Robotics Lab

Incorporating state-of-the-art deep learning approaches to augment conventional soft robotic simulations for a fast, accurate and useful simulation for real soft robots.

Keywords

Soft Robotics, Machine Learning, Physical Modeling, Simulation

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Published since: 2025-03-02 , Earliest start: 2025-03-01 , Latest end: 2026-03-01

Organization Soft Robotics Lab

Hosts Michelis Mike , Katzschmann Robert, Prof. Dr.

Topics Information, Computing and Communication Sciences , Engineering and Technology

Generating Realistic Event Camera Data with Generative AI

Robotics and Perception

In this project, the student applies concepts from current advances in image generation to create artificial events from standard frames. Multiple state-of-the-art deep learning methods will be explored in the scope of this project.

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Computer Vision, Event Cameras, Deep Learning

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Published since: 2025-02-10 , Earliest start: 2024-12-12

Organization Robotics and Perception

Hosts Messikommer Nico

Topics Information, Computing and Communication Sciences

Enhancing Robotic Motor Policies with Event Cameras

Robotics and Perception

The goal of this project is to develop a shared embedding space for events and frames, enabling the training of a motor policy on simulated frames and deployment on real-world event data.

Keywords

Computer Vision, Event Cameras, Robotics, Unsupervised Domain Adaption

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Published since: 2025-02-10 , Earliest start: 2024-12-12

Organization Robotics and Perception

Hosts Messikommer Nico

Topics Information, Computing and Communication Sciences

Designing Freeform Trajectories through Acoustic Streaming and Artificial Intelligence

Acoustic Robotics for Life Sciences and Healthcare (ARSL)

The manipulation of materials and fluids through acoustic streaming has emerged as a powerful technique with applications in manufacturing and biomedical engineering. This method utilizes sound waves to control the movement of particles within a fluid, offering precise and non-invasive manipulation. However, achieving freeform path manipulation—guiding materials along complex, non-linear trajectories—remains a significant challenge due to difficulties in controlling the influence range and vortex dynamics of acoustic streaming. Traditional methods often struggle with maintaining precision and stability along intricate paths, as the non-uniform distribution of acoustic forces complicates consistent directionality. Artificial Intelligence (AI) presents a promising solution, enabling real-time control and optimization of these systems. By integrating AI with acoustic streaming, algorithms can analyze and predict the interactions between acoustic forces and fluid dynamics, allowing for dynamic adjustments that enhance accuracy. In this thesis, we propose addressing these challenges by implementing a pillar array of acoustic actuators coupled with AI-driven control systems. The pillar array will generate and modulate acoustic streaming fields, while AI will optimize and automate their control in real time. This integration aims to improve the precision of freeform path manipulation, facilitating the creation of complex patterns that are otherwise difficult to achieve, thereby expanding the possibilities for material manipulation across various applications.

Keywords

Freeform path; Manipulation; Ultrasound; pillar array; AI

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Published since: 2025-02-05 , Earliest start: 2025-02-06 , Latest end: 2025-09-30

Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)

Hosts Deng Yong

Topics Engineering and Technology

Computational Modeling of Muscle Dynamics for Biohybrid Robots

Soft Robotics Lab

This research aims to advance biohybrid robotics by integrating living biological components with artificial materials. The focus is on developing computational models for artificial muscle cells, a critical element in creating biohybrid robots. Challenges include modeling the complex and nonlinear nature of biological muscles, considering factors like elasticity and muscle fatigue, as well as accounting for fluid-structure interaction in the artificial muscle's environment. The research combines first principle soft body simulation methods and machine learning to improve understanding and control of biohybrid systems.

Keywords

Biohybrid Robotics, Computational Models, Soft Body Simulation, Finite Element Method (FEM), Muscle Dynamics, Soft Robotics

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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01

Organization Soft Robotics Lab

Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.

Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Biology , Physics

GPU Acceleration of Soft Robot Modeling: Enhancing Performance with CUDA

Soft Robotics Lab

We are enhancing soft robot modeling by developing a GPU-accelerated version of our FEM-based framework using CUDA. This research focuses on optimizing parallel computations to significantly speed up simulations, enabling larger problem sizes and real-time control. By improving computational efficiency, we aim to advance soft robotics research and facilitate more detailed, dynamic simulations.

Keywords

Soft Body Simulation, high-performance computing, GPU programming, Parallel Computing, Finite Element Method (FEM), Multiphysics Simulation

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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01

Organization Soft Robotics Lab

Hosts Katzschmann Robert, Prof. Dr. , Mekkattu Manuel

Topics Information, Computing and Communication Sciences , Engineering and Technology

Advancing Soft Robot Modeling: Integrating Physics, Optimization, and Control

Soft Robotics Lab

We are advancing soft robot simulation with FEM and energy-based methods to model complex, adaptive behaviors. This research entails developing the framework to support diverse designs, integrate new physics models, and optimize performance, enabling enhanced control and real-world applications of soft robots.

Keywords

Soft Robotics, Finite Element Method (FEM), Physical Modeling, Benchmarking, Optimization, Multiphysics Simulation, Sim-to-Real

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Published since: 2025-02-04 , Earliest start: 2025-02-01 , Latest end: 2026-02-01

Organization Soft Robotics Lab

Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.

Topics Information, Computing and Communication Sciences , Engineering and Technology

Reinforcement Learning for Excavation Planning In Terra

Robotic Systems Lab

We aim to develop a reinforcement learning-based global excavation planner that can plan for the long term and execute a wide range of excavation geometries. The system will be deployed on our legged excavator.

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Keywords: Reinforcement learning, task planning

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Published since: 2025-02-03 , Earliest start: 2025-07-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Terenzi Lorenzo

Topics Information, Computing and Communication Sciences

Model Based Reinforcement Learning

Robotic Systems Lab

We want to train an excavator agent to learn in a variety of soil using a fast, GPU-accelerated soil particle simulator in Isaac Sim.

Keywords

particle simulation, omniverse, warp, reinforcement learning, model based reinforcement learning.

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Published since: 2025-02-03 , Earliest start: 2025-06-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Egli Pascal Arturo , Terenzi Lorenzo

Topics Information, Computing and Communication Sciences , Engineering and Technology

Reinforcement Learning for Particle-Based Excavation in Isaac Sim

Robotic Systems Lab

We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim.

Keywords

particle simulation, omniverse, warp, reinforcement learning

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Published since: 2025-02-03 , Earliest start: 2025-06-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Egli Pascal Arturo , Mittal Mayank , Terenzi Lorenzo

Topics Information, Computing and Communication Sciences

Perceptive Reinforcement Learning for Exavation

Robotic Systems Lab

In this project, our goal is to leverage precomputed embeddings(VAE in Isaacsim) from 3D earthworks scene reconstructions to train reinforcement learning agents. These embeddings, derived from incomplete point cloud data and reconstructed using an encoder-decoder neural network, will serve as latent representations. The main emphasis is on utilizing these representations to develop and train reinforcement learning policies for digging tasks.

Keywords

LIDAR, 3D reconstruction, Isaac gym, deep learning, perception, reinforcement learning

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Published since: 2025-02-03 , Earliest start: 2025-06-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Höller David , Terenzi Lorenzo

Topics Information, Computing and Communication Sciences

Reiforcement Learning of Pretrained Trasformer Models

Robotic Systems Lab

We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim.

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Keywords: particle simulation, omniverse, warp, reinforcement learning

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Published since: 2025-02-03 , Earliest start: 2025-07-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Terenzi Lorenzo

Topics Information, Computing and Communication Sciences

Multiagent Reinforcement Learning in Terra

Robotic Systems Lab

We want to train multiple agents in the Terra environment, a fully end-to-end GPU-accelerated environment for RL training.

Keywords

multiagent reinforcement learning, jax, deep learning, planning

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Published since: 2025-02-03 , Earliest start: 2025-07-01 , Latest end: 2025-12-31

Organization Robotic Systems Lab

Hosts Terenzi Lorenzo

Topics Information, Computing and Communication Sciences

A Bayesian sensor fusion and machine learning approach for robust hand gesture decoding with application to stroke rehabilitation.

Sensory-Motor Systems Lab

About the project: This thesis aims to design a framework for robust fine-motor action decoding using multi-modal (sEMG and depth sensing camera) Bayesian sensor fusion and machine learning approach

Keywords

Bayesian inference, sEMG, depth sensing camera, rehabilitation, machine learning, deep transfer learning

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Published since: 2025-02-01 , Earliest start: 2025-03-01 , Latest end: 2025-08-01

Organization Sensory-Motor Systems Lab

Hosts Dash Adyasha

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Automatic Failure Detection for Drones

Robotics and Perception

Automatic failure detection is an essential topic for aerial robots as small failures can already lead to catastrophic crashes. Classical methods in fault detection typically use a system model as a reference and check that the observed system dynamics are within a certain error margin. In this project, we want to explore sequence modeling as an alternative approach that feeds all available sensor data into a neural network. The network will be pre-trained on simulation data and finetuned on real-world flight data. Such a machine learning-based approach has significant potential because neural networks are very good at picking up patterns in the data that are hidden/invisible to hand-crafted detection algorithms.

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Published since: 2025-01-30 , Earliest start: 2025-02-01 , Latest end: 2026-01-31

Organization Robotics and Perception

Hosts Bauersfeld Leonard

Topics Engineering and Technology

Event-based Particle Image Velocimetry

Robotics and Perception

When drones are operated in industrial environments, they are often flown in close proximity to large structures, such as bridges, buildings or ballast tanks. In those applications, the interactions of the induced flow produced by the drone’s propellers with the surrounding structures are significant and pose challenges to the stability and control of the vehicle. A common methodology to measure the airflow is particle image velocimetry (PIV). Here, smoke and small particles suspended in the surrounding air are tracked to estimate the flow field. In this project, we aim to leverage the high temporal resolution of event cameras to perform smoke-PIV, overcoming the main limitation of frame-based cameras in PIV setups. Applicants should have a strong background in machine learning and programming with Python/C++. Experience in fluid mechanics is beneficial but not a hard requirement.

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Published since: 2025-01-30 , Earliest start: 2024-07-01 , Latest end: 2025-03-01

Organization Robotics and Perception

Hosts Bauersfeld Leonard

Topics Information, Computing and Communication Sciences , Engineering and Technology

Diffusion-based Shared Autonomy System for Telemanipulation

Robotic Systems Lab

Robots may not be able to complete tasks fully autonomously in unstructured or unseen environments, however direct teleoperation from human operators may also be challenging due to the difficulty of providing full situational awareness to the operator as well as degradation in communication leading to the loss of control authority. This motivates the use of shared autonomy for assisting the operator thereby enhancing the performance during the task. In this project, we aim to develop a shared autonomy framework for teleoperation of manipulator arms, to assist non-expert users or in the presence of degraded communication. Imitation learning, such as diffusion models, have emerged as a popular and scalable approach for learning manipulation tasks [1, 2]. Additionally, recent works have combined this with partial diffusion to enable shared autonomy [3]. However, the tasks were restricted to simple 2D domains. In this project, we wish to extend previous work in the lab using diffusion-based imitation learning, to enable shared autonomy for non-expert users to complete unseen tasks or in degraded communication environments.

Keywords

Imitation learning, Robotics, Manipulation, Teleoperation

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Semester Project , ETH Zurich (ETHZ)

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Published since: 2024-12-02 , Earliest start: 2024-11-01 , Latest end: 2025-11-01

Applications limited to ETH Zurich , University of Zurich

Organization Robotic Systems Lab

Hosts Elanjimattathil Aravind

Topics Information, Computing and Communication Sciences , Engineering and Technology

Deep Reinforcement Learning to Control Microrobots in 3D Dynamic Flow Environments

Acoustic Robotics for Life Sciences and Healthcare (ARSL)

Identifying effective control strategies for the automation of acoustic robotic systems is challenging in a microfluidic environment. This project focuses on reinforcement learning (RL) to control microrobots in chaotic microfluidic flow and vortices.

Keywords

Reinforcement learning, Artificial Intelligence, Ultrasound, Fluid control

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Published since: 2024-08-05 , Earliest start: 2024-08-05 , Latest end: 2025-06-30

Organization Acoustic Robotics for Life Sciences and Healthcare (ARSL)

Hosts Medany Mahmoud

Topics Information, Computing and Communication Sciences , Engineering and Technology

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