Semester Project
Semester Projects at IRIS
Spatially-Enhanced Linear-Attention Transformer for End-to-End Navigation
Transformer architectures have proven highly effective in sequence modelling, but their standard self-attention mechanism suffers from quadratic complexity in sequence length. The work by Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention (Katharopoulos et al., 2020) shows how self-attention can be reformulated as kernel feature maps with a linear complexity implementation. Separately, in navigation and robotics, end-to-end learning of navigation policies (e.g., via reinforcement learning) has shown strong promise; however, many architectures (such as standard RNNs) struggle to build spatial memory — that is, integrating observations from different viewpoints into a coherent spatial representation. For example, the recent work Spatially‑Enhanced Recurrent Memory for Long‑Range Mapless Navigation via End‑to‑End Reinforcement Learning (Yang et al., 2025) proposes Spatially-Enhanced Recurrent Units (SRUs) to address this. This motivates the question: can we combine the efficiency and scalability of linear-attention transformers with a spatial-enhancement mechanism tailored for navigation, thereby achieving end-to-end navigation with long-term spatial memory and efficient inference?
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-10-28 , Earliest start: 2025-11-15 , Latest end: 2025-12-15
Organization Robotic Systems Lab
Hosts Yang Fan
Topics Information, Computing and Communication Sciences
Learning-Based Decoding for Event Cameras
Develop a learning-based decoder for event cameras to facilitate efficient real-world tasks.
Keywords
Event-based Vision, Streaming Algorithms, CPU, GPU, Encoder-Decoder Learning, Encoding, Decoding, Machine Learning
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Semester Project , Master Thesis
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Published since: 2025-10-21
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Mathematical Sciences , Engineering and Technology
Instrumentation of ice hockey skates to determine on ice performance
This semester or master thesis aims to instrument ice hockey skates to enable direct measurement of three-dimensional forces exerted by competitive ice hockey players on the ice during training and test scenarios.
Keywords
sports engineering, portable force transducer, ice hockey, skate instrumentation
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Semester Project , Master Thesis
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Published since: 2025-10-17 , Earliest start: 2026-01-05 , Latest end: 2026-09-15
Applications limited to ETH Zurich
Organization Sensory-Motor Systems Lab
Hosts Wolf Peter
Topics Engineering and Technology
Smart Microcapsules for Biomedical Advances
This Master's thesis/semester project focuses on the microfluidic fabrication of microcapsules with multi-environmental responsiveness. The aim is to develop microcapsule-based microrobots capable of adapting to various environmental cues. We envision that these microrobots will be used for complex tasks in biomedical applications.
Keywords
Microfluidics, Microcapsules, Microrobotics, Responsive Polymers, Biomedical Engineering
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Semester Project , Internship , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-10-14 , Earliest start: 2026-01-19
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Intelligent Micromachines Made from Droplet-Based Factory
We invite applications for a Master's thesis / semester project that focuses on the fabrication of microrobots with custom shapes. Using our developed droplet printing technique, this project will explore how different microrobot shapes, created by different magnetic fields and materials, influence their control behaviors in blood vessels. This research aims to advance biomedical technologies, particularly in targeted drug delivery and minimally invasive procedures.
Keywords
Microrobotics, 4D Printing, Soft Materials, Biomedical Devices
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Semester Project , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-10-14 , Earliest start: 2026-02-02
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Engineering and Technology , Chemistry
Wireless Motion and Health Monitoring with Triboelectric Nanogenerators using a Custom Readout Circuit
This project aims to design and realize a custom single-PCB wireless readout circuit optimized for triboelectric nanogenerators (TENGs) for motion and health monitoring. Unlike previous designs that relied on assembling multiple commercial off-the-shelf PCBs, this project will integrate the functionalities of signal conditioning, energy harvesting, and wireless data transmission onto one compact, low-power circuit board). This PCB will be used to facilitate wireless joint angle analysis and fatigue monitoring during repetitive human movements using machine learning and deep learning.
Keywords
TENG, energy harvesting, wireless circuits, PCB design, low-power electronics, sensors, movement, mobile health, wearables
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Semester Project , Master Thesis
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Published since: 2025-10-14 , Earliest start: 2025-10-01 , Latest end: 2026-08-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics 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
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Semester Project , Internship , Master Thesis
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Published since: 2025-10-14 , 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
Learning-based object orientation prediction for handovers
Humans are exceptional at handovers. Besides timing and spatial precision, they also have a high-level understanding of how the other person wants to use the object that is handed over. This information is needed to hand over an object, such that it can be used directly for a specific task. While robots can reason about grasp affordances, the integration of this information with perception and control is missing.
Keywords
Robot-Human Handover, Human-Robot-Interaction, Mobile Manipulation, Robotics
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Semester Project , Master Thesis
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Published since: 2025-10-13 , Earliest start: 2025-02-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Scheidemann Carmen , Tulbure Andreea
Topics Information, Computing and Communication Sciences , Engineering and Technology
Fine-tuning Policies in the Real World with Reinforcement Learning
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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Semester Project , Master Thesis
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Published since: 2025-10-13 , 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
Use Inverse Reinforcement Learning (IRL) to learn reward functions from previous expert drone demonstrations.
Keywords
Inverse Reinforcement Learning, Drones, Robotics
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Semester Project , Master Thesis
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Published since: 2025-10-13 , 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
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: 2025-10-13
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Tulbure Andreea
Topics Information, Computing and Communication Sciences
Smart Stretchable Piezoelectric Hydrogels: From Joint Motion to Bioelectric Stimulation
We are developing an intelligent composite material composed of piezoelectric nanoparticles embedded in a stretchable hydrogel matrix with a kirigami-inspired design. Mechanical deformation activates the piezoelectric nanoparticles, generating bioelectric signals (like Pikachu) that can stimulate cell differentiation. This self-powered system shows promise for biomedical applications.
Keywords
Flexible electrodes optimization, piezoelectric mesh, biomedical applications.
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Semester Project , Master Thesis
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Published since: 2025-10-09 , Earliest start: 2025-09-01 , Latest end: 2026-09-01
Organization Multiscale Robotics Lab
Hosts Chen Huimin
Topics Engineering and Technology
Efficient data processing and reporting in stroke neuro-rehabilitation
Project goal is to optimise existing and develop new algorithms into an efficient system for signal pre-processing, data storage, analysis and visualization in motor-neurorehabilitation. This data is generated by stroke patients wearing motion sensors during their therapy sessions. Key endpoint of the project is to display real-time and longitudinal therapy results, which can aid therapists and patients. The results of the project will help develop a more efficient therapy and is a key part of a larger project that seeks to develop an intelligent and closed-loop neural stimulation system for stroke rehabilitation.
Keywords
health biomarkers, data science, computer science, data visualization, data processing, real-time, internet of medical things, IoMT, healthcare internet of things, healthcare IoT
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Semester Project , Internship , Master Thesis
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Published since: 2025-10-08 , Earliest start: 2023-05-09
Organization Rehabilitation Engineering Lab
Hosts Donegan Dane , Viskaitis Paulius
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
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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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-10-05 , Earliest start: 2025-11-01 , Latest end: 2026-06-01
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Bhardwaj Arjun , Zurbrügg René
Topics Information, Computing and Communication Sciences
Evaluating Engagement and Adherence to Robot-Assisted Rehabilitation: Can Large Language Model-Based Conversational Agents Support Stroke and TBI Patients During Unsupervised Therapy?
Stroke and traumatic brain injury (TBI) are major causes of long-term disability, often requiring intensive rehabilitation to restore motor function, particularly in the hands. While robotic-assisted therapy and mobile health (mHealth) applications offer promising tools for recovery, sustaining patient engagement outside clinical environments remains a significant challenge. This project explores the use of the RehabCoach app and ReHandyBot device in a hybrid rehabilitation program (i.e., two weeks in-clinic followed by six weeks of unsupervised home therapy). The focus is on collecting and analyzing conversational data between patients and the app’s large language model (LLM)-based conversational agent to evaluate how these interactions influence therapy adherence and engagement.
Keywords
Stroke rehabilitation, traumatic brain injury, mobile health, conversational AI, large language models, therapy adherence, unsupervised rehabilitation
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Semester Project , Master Thesis
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Published since: 2025-10-02 , Earliest start: 2025-11-16 , Latest end: 2026-09-30
Organization Rehabilitation Engineering Lab
Hosts Retevoi Alexandra
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Deep Learning of Residual Physics For Soft Robot Simulation
Incorporating state-of-the-art deep learning approaches to augment conventional soft robotic simulations for a fast, accurate and useful simulation for real soft robots.
Keywords
Soft Robotics, Machine Learning, Physical Modeling, Simulation
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Semester Project , Master Thesis
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Published since: 2025-09-30 , 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
Integrating Event-based Vision Capabilities into LLMs
This project explores integrating event-based vision into LLMs through custom layers and knowledge distillation, enabling efficient processing of sparse, asynchronous data for dynamic scene understanding in real-world applications.
Keywords
Event-based vision, large language models, multimodal AI, asynchronous data, sparse representation, high-dynamic range, fast motion, event cameras, knowledge distillation, autonomous navigation, human-robot interaction.
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Semester Project , Master Thesis
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Published since: 2025-09-23
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Event Representation Learning for Control with Visual Distractors
This project develops event-based representation learning methods for control tasks in environments with visual distractors, leveraging sparse, high-temporal-resolution event data to improve robustness and efficiency over traditional frame-based approaches.
Keywords
Event-based vision, representation learning, control policies, reinforcement learning, visual distractors, high-dynamic range, motion blur, sparse data, robust perception, locomotion, navigation.
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Semester Project , Master Thesis
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Published since: 2025-09-23
Organization Robotics and Perception
Hosts Zubic Nikola
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Serial Manufacturing Platform for Magnetic Endovascular Devices
Electromagnetic navigation systems enable steerable endovascular devices to access previously unreachable brain regions for stroke and aneurysm treatment. This project develops a manufacturing setup for scalable production of these devices, followed by fabrication and testing to advance next-generation neurovascular therapies.
Keywords
Mechanical Engineering, Medical Robotics, Mechanical Design
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-09-22 , Earliest start: 2025-09-22 , Latest end: 2026-04-01
Organization Multiscale Robotics Lab
Hosts Gantenbein Valentin
Topics Engineering and Technology
Radiometric Calibration for LiDAR Inertial Odometry
This project aims to adapt radiometric calibration techniques to robotics-grade LiDAR sensors to correct inconsistencies in intensity values caused by distance and incidence-angle effects. By producing more consistent LiDAR intensity images, the project seeks to enhance the robustness and accuracy of LiDAR Inertial Odometry (LIO) for localization and mapping.
Keywords
Robotics, LiDAR, Odometry, Calibration, State Estimation, Localization, Mapping
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Published since: 2025-09-15 , Earliest start: 2025-09-21 , Latest end: 2026-04-30
Organization Autonomous Systems Lab
Hosts Pfreundschuh Patrick
Topics Information, Computing and Communication Sciences , Engineering and Technology
Custom Wireless Readout Circuit for Triboelectric Nanogenerator (TENG) Sensing and Energy Harvesting
This project aims to design and realize a custom single-PCB wireless readout circuit optimized for triboelectric nanogenerators (TENGs). Unlike previous designs that relied on assembling multiple commercial off-the-shelf PCBs, this project will integrate the functionalities of signal conditioning, energy harvesting, and wireless data transmission onto one compact, low-power circuit board.
Keywords
TENG, energy harvesting, wireless circuits, PCB design, low-power electronics, sensors
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Published since: 2025-09-12 , Earliest start: 2025-10-01 , Latest end: 2026-08-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Zada Muhammad
Topics Engineering and Technology
Development of a robotic hand actuated using soft HASEL actuators
Development of a forearm to actuate a tendon driven humanoid robotic hand using soft electrostatic HASEL actuator and demonstration of its capabilities with a Franka robotic arm.
Keywords
Electrostatic actuator, soft actuator, Robotic Hands, Soft Robotics
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Published since: 2025-09-12 , Earliest start: 2025-09-22 , Latest end: 2025-12-01
Organization Soft Robotics Lab
Hosts Kazemipour Amirhossein , Hinchet Ronan , Katzschmann Robert, Prof. Dr.
Topics Engineering and Technology
Learning Precise Force Estimation Under Dynamic Loads
Force estimation on robotic arms is valuable for performing mobile manipulation tasks, such as pick-and-place or playing badminton. However, at high speeds, traditional methods such as momentum-based observers break down due to compounding errors in the dynamic model. Recent works have proposed using LSTMs to apply either a residual to a momentum based observer, or outright replace it with a learned model. However, the problem of doing this at high velocities remains relatively unexplored. In this project, you will develop a data-driven model for estimating forces during dynamic trajectories. You will investigate different model architectures and learning approaches.
Keywords
force estimation, machine learning, robotics
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Semester Project , Master Thesis
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Published since: 2025-09-11 , Earliest start: 2025-09-14
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Organization Robotic Systems Lab
Hosts Fischer Oliver
Topics Engineering and Technology
Simulation of cellular-force-microscopy-integrated lab-on-a-chip devices for in-situ biohybrid microrobot characterization
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 and have proven beneficial for the large-scale production of biohybrid magnetic microrobots. Integrating the LoC devices with the cellular force microscope (CFM) allows for real-time monitoring and in-situ mechanical characterization of biohybrid magnetic microrobots during their production and incubation. The goal of this project is to design and simulate an intelligent LoC/OoC device integrated with CFM for in-situ monitoring and characterization during microrobot production and drug testing.
Keywords
Lab-on-a-chip, organ-on-a-chip, magnetic microrobot, cellular force microscope, simulation
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Semester Project , Bachelor Thesis
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Published since: 2025-09-09 , Earliest start: 2025-09-09 , Latest end: 2026-03-31
Organization Multiscale Robotics Lab
Hosts Zhu Jiawei
Topics Engineering and Technology
Informed Exploration in Reinforcement Learning via Sampling-Based Planning
Robust locomotion across diverse terrains remains one of the most challenging and exciting problems in legged robotics. While deep reinforcement learning (RL) has enabled impressive quadrupedal behaviors, generalization to unseen or complex terrains often suffers from low sample efficiency. To address this, researchers typically rely on labor-intensive curriculum design, where training terrains are manually structured to progress from easy to difficult, while trying to avoid catastrophic forgetting. These staged curricula allow the RL agent to master simple environments before tackling more complex ones. However, even with such manually designed curricula, RL training can take several days. This is partly because the agent does not retain knowledge about where it has succeeded or failed, nor does it use this experience to inform future exploration. This project aims to develop an automated approach to guide the RL exploration by leveraging sampling-based planning techniques. We formulate the training process as a graph expansion problem, wherein the terrain space is incrementally explored to maximize gains in locomotion robustness and performance. Can the Voronoi bias inherent in sampling-based planning steer the agent toward more effective and sample-efficient training trajectories? If successful, this approach could enable the use of real-world terrain scans for locomotion training, reducing dependence on expert-designed environments and substantially accelerating the training process. The project brings together concepts from sampling-based planning, adaptive curricula, and locomotion learning.
Keywords
Curriculum Learning, Quadruped Locomotion, Sampling-Based Planning, Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-09-05
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Zurich
Organization Robotic Systems Lab
Hosts Klemm Victor , Qu Kaixian
Topics Information, Computing and Communication Sciences
Event-based Object Segmentation for Vision-Guided Autonomous Systems
This project develops an end-to-end pipeline for object segmentation using event camera data, leveraging their microsecond latency, high dynamic range, and sparse asynchronous output to overcome the limitations of frame-based vision. By combining advanced deep learning architectures with rigorous benchmarking, the approach aims to deliver accurate, temporally consistent, and robust segmentation for real-time applications in navigation and control.
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Semester Project , Master Thesis
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Published since: 2025-09-05 , Earliest start: 2025-09-05 , Latest end: 2026-12-01
Organization Robotics and Perception
Hosts Pellerito Roberto
Topics Engineering and Technology
Novel Learning Paradigms for Low-latency and Efficient Vision
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: 2025-09-05 , Earliest start: 2024-12-12
Organization Robotics and Perception
Hosts Pellerito Roberto , Messikommer Nico
Topics Information, Computing and Communication Sciences
Vision Language Action models for Drones
This project explores generative modeling of drone flight paths conditioned on natural language commands and spatial constraints, aiming to produce plausible 3D trajectories for training reinforcement learning policies. We investigate model architectures, data sources, and trajectory extraction methods to ensure generated paths are both physically feasible and stylistically aligned with textual descriptions.
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Semester Project , Master Thesis
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Published since: 2025-09-05 , Earliest start: 2025-09-05 , Latest end: 2026-12-01
Organization Robotics and Perception
Hosts Pellerito Roberto
Topics Information, Computing and Communication Sciences , Engineering and Technology
Event-Based Tactile Sensor for Humanoid Robotic Hands
Humanoid robots require tactile sensing to achieve robust dexterous manipulation beyond the limits of vision-based perception. This project develops an event-based tactile sensor to provide low-power, high-bandwidth force estimation from material deformation, with the goal of integrating it into a human-scale robotic hand.
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Semester Project , Master Thesis
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Published since: 2025-09-05 , Earliest start: 2026-01-05 , Latest end: 2026-12-01
Organization Robotics and Perception
Hosts Pellerito Roberto
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Real-time control of neural stimulation for stroke patients.
Real-time analysis of movement kinematics can benefit multiple different strategies in rehabilitation after stroke, including allowing closed-loop brain stimulation. Use of inertial measurement units (IMUs) allows detection of movement and extraction of kinematic features, but application in real-time remains challenging. This project will develop algorithms for real-time movement data analysis and feature extraction in typical rehabilitation tasks and general real-life movements. In turn, these algorithms will be applied to control novel brain stimulation approaches in stroke neurorehabilitation.
Keywords
Inertial measurement unit, IMU, movement tracking, machine learning, real-time, signal processing
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Semester Project , Master Thesis
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Published since: 2025-09-02 , Earliest start: 2023-05-09
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius , Donegan Dane
Topics Engineering and Technology
Self-locking cuff electrodes for the nerve stimulation
Nerve cuff electrodes are designed for reliable recording and stimulation of peripheral nerves, as illustrated in Figure A. This project aims to develop a wireless, self-locking cuff electrode tailored specifically for nerve stimulation, as depicted in Figure B&C.
Keywords
Flexible electrodes design, FEM simulation, Biomedical applications
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Semester Project , Master Thesis
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Published since: 2025-09-01 , Earliest start: 2025-09-01 , Latest end: 2026-09-01
Organization Multiscale Robotics Lab
Hosts Chen Huimin
Topics Engineering and Technology
Reflection and Ghosting Removal with Event Streams
This project explores leveraging event-camera signals to suppress reflections and ghosting in images captured through glass or other reflective surfaces. By exploiting temporal and motion differences between scene content and reflection artifacts, the goal is to disentangle true scene information from distracting overlays.
Keywords
Event cameras, reflection removal, ghosting suppression, image restoration, computational photography, event-based vision
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Semester Project , Master Thesis
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Published since: 2025-09-01 , Earliest start: 2025-09-01
Organization Robotics and Perception
Hosts Zou Rong
Topics Information, Computing and Communication Sciences , Engineering and Technology
Reinforcement Learning for Magnetic Levitation
This project explores the control of freely levitating objects in space using electromagnetic navigation using reinforcement learning. By generating controlled magnetic fields, we can wirelessly manipulate the position and orientation of the levitating magnetic object. A fully functional experimental platform is already available, providing a rich testbed for exploring advanced control strategies.
Keywords
reinforcement learning
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-09-01 , Earliest start: 2025-09-02 , Latest end: 2026-12-31
Organization Multiscale Robotics Lab
Hosts Zughaibi Jasan
Topics Engineering and Technology
Event-based Occlusion Suppression for Robust Detection and VO in Adverse Weather
This project explores the effect of dynamic occlusions on the performance of event-based detection and VO algorithms. It involves the development of low-latency suppression strategies that mitigate such effects, restoring robust perception in adverse weather.
Keywords
Event cameras, occlusion suppression, visual odometry, object detection, adverse weather, event-based vision
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Semester Project , Master Thesis
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Published since: 2025-09-01 , Earliest start: 2025-09-01
Organization Robotics and Perception
Hosts Zou Rong
Topics Information, Computing and Communication Sciences , Engineering and Technology
Advancing Vibrotactile Sensory Stimulation for Brain Imaging
Design of comfortable textiles and stimulation protocol for a pneumatic, MRI-compatible vibrotactile stimulator
Keywords
touch sensation, tactile illusions, neurorehabilitation, MRI
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Semester Project , Internship , Master Thesis
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Published since: 2025-08-28 , Earliest start: 2025-09-15 , Latest end: 2026-06-26
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Sensory-Motor Systems Lab
Hosts Wolf Peter
Topics Medical and Health 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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Semester Project , Internship , Bachelor Thesis
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Published since: 2025-08-27 , 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
Better Scaling Laws for Neuromorphic Systems
This project explores and extends the novel "deep state-space models" framework by leveraging their transfer function representations.
Keywords
deep learning, state space models, transfer function, parameterizations, S4 model, Fourier Transform, Convolution, Neuromorphic Systems, Neuromorphic, Sequence Modeling, Event-based Vision
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Semester Project , Master Thesis
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Published since: 2025-08-26
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
Foundation models for generalizable construction machine automation
Autonomous operation of heavy construction machinery promises major gains in safety, efficiency, and scalability for the multi-trillion-dollar construction industry. Excavators present a unique challenge, combining the navigation demands of autonomous driving with the precision of robotic manipulation in unstructured, dynamic environments. This project explores Vision-Language-Action (VLA) and diffusion-based policy learning to develop generalizable excavation policies. Leveraging large-scale demonstration data naturally collected during human operation, we aim to train multimodal control models capable of adapting across sites, lighting conditions, and machine types. The approach will be evaluated through simulation benchmarks and, if possible, real-world trials, advancing the path toward scalable, generalist autonomy for robotic construction.
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Published since: 2025-08-12 , Earliest start: 2025-08-31 , Latest end: 2026-03-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Robotic Systems Lab
Hosts Nan Fang , Zhang Weixuan
Topics Engineering and Technology
ADHD-Biomarker Study: Software development of Data Collection and Data Management Structures
The Rehabilitation Engineering Laboratory (ReLab), ETH Zurich is running a paediatric study that integrates fNIRS, EEG, eye-tracking and motion sensing to establish objective biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD). You will create the technical backbone of a multimodal data-collection setup – coding computerized attention tests, synchronizing hardware, and delivering clean, well-documented datasets for downstream research.
Keywords
ADHD, Biomarker, fNIRS, EEG, Eye-tracking, Motion sensing, Data collection, Data management, Software engineering
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Semester Project , Course Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-08-08 , Earliest start: 2025-08-10 , Latest end: 2026-03-31
Organization Rehabilitation Engineering Lab
Hosts Schönhammer Josef
Topics Medical and Health Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
ADHD-Biomarker Study: Neuropsychological Task Development and Data Analytics
The Rehabilitation Engineering Laboratory (ReLab), ETH Zurich is running a pediatric study that integrates fNIRS, EEG, eye-tracking and motion sensing to establish objective biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD). You will drive the scientific backbone of the project – optimizing child-specific task parameters, leading participant interaction, and conducting and presenting statistical analyses.
Keywords
ADHD, Biomarkers, Neuropsychology, fNIRS, EEG, Eye-tracking, Motion Capture, Data Analytics, Statistical Analysis
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Semester Project , Course Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-08-08 , Earliest start: 2025-08-10 , Latest end: 2026-03-31
Organization Rehabilitation Engineering Lab
Hosts Schönhammer Josef
Topics Medical and Health Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Learning-based Control for Magnetic Levitation
This project explores the control of freely levitating objects in space using electromagnetic navigation, as illustrated in the image above. By generating controlled magnetic fields, we can wirelessly manipulate the position and orientation of the levitating magnetic object. A fully functional experimental platform is already available, providing a rich testbed for exploring advanced control strategies.
Keywords
magnetic levitation control, learning-based control, Model Predictive Control
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-08-06 , Earliest start: 2025-08-07 , Latest end: 2026-12-31
Organization Multiscale Robotics Lab
Hosts Zughaibi Jasan
Topics Engineering and Technology
Mechanistic Evaluation of taVNS in Motor Adaptation for Stroke Rehabilitation
This study aims to evaluate the mechanisms by which transauricular vagus nerve stimulation (taVNS) may facilitate motor learning and adaptation, focusing on reticulospinal tract (RST) activation. A set of assessments will be used to build a comprehensive neurophysiological profile, providing insights relevant to developing taVNS-based clinical interventions. In this role, you will engage in study design, data collection, and analysis, gaining hands-on experience in mechanistic neurophysiological research with direct clinical applications.
Keywords
Transauricular vagus nerve stimulation (taVNS) Reticulospinal tract (RST) Motor learning StartReact paradigm Stroke rehabilitation Neurophysiology Multisite EMG Motor pathway activation Clinical neurostimulation
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-08-04 , Earliest start: 2024-11-24 , Latest end: 2025-10-26
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Medical and Health Sciences , Engineering and Technology
Reiforcement Learning of Pretrained Trasformer Models
We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim.
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Keywords: particle simulation, omniverse, warp, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-07-29 , Earliest start: 2025-09-01 , Latest end: 2026-03-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Multiagent Reinforcement Learning in Terra
We want to train multiple agents in the Terra environment, a fully end-to-end GPU-accelerated environment for RL training.
Keywords
multiagent reinforcement learning, jax, deep learning, planning
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Semester Project , Master Thesis
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Published since: 2025-07-29 , Earliest start: 2025-09-01 , Latest end: 2026-03-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Bimanual Dexterity: Coordinated Dual-Arm Policies for Dexterous Object Manipulation
Dexterous bimanual manipulation remains a difficult challenge, requiring tight coordination between both arms and hands—especially when handling large objects. While humans perform such tasks effortlessly, robotic systems often lack the precision and adaptability needed. This project aims to tackle this problem by learning coordinated dual-arm and hand policies from a few human demonstrations, followed by reinforcement learning in simulation for real-world deployment.
Keywords
Dexterous Manipulation, Bimanual Manipulation, Learning from Demonstrations, Reinforcement Learning, Humanoid Robotics
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Semester Project , Master Thesis
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Published since: 2025-07-25 , Earliest start: 2025-07-28 , Latest end: 2026-05-31
Organization Robotic Systems Lab
Hosts He Junzhe , Mittal Mayank , Bhardwaj Arjun
Topics Information, Computing and Communication Sciences
From Grasp to Twist: Composing Dexterous Grasping and In-Hand Manipulation under Motion
Dexterous in-hand manipulation has advanced rapidly, yet most approaches assume the object is already grasped or the hand is fixed in place—conditions rarely met in real-world scenarios. This project addresses the challenge of enabling robots to both grasp and manipulate objects dynamically by learning modular skills that can be coordinated for effective manipulation under motion.
Keywords
Dexterous Manipulation, Reinforcement Learning, Skill Learning
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Semester Project , Master Thesis
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Published since: 2025-07-25 , Earliest start: 2025-07-28 , Latest end: 2026-05-31
Organization Robotic Systems Lab
Hosts Bhardwaj Arjun , Zurbrügg René , Mittal Mayank
Topics Information, Computing and Communication Sciences
Development of flexible, biocompatible electrodes for vagus nerve stimulation therapy
Stroke is the most common cause of disability and as many as 14 million people suffer a stroke every year. Typical therapy today is focused on physical exercises and rarely combats the core of the problem - the interactions between the motor actions and the activity patterns of the injured brain. Therefore, we are developing a cutting-edge medical device that helps combine physical therapy with a non-invasive brain stimulation. This is expected to boost recovery after stroke and make this advanced neuro-therapy accessible to millions of people who need it.
Keywords
Biocompatibility Conductive Materials Vagus Nerve Stimulation (VNS) Transcutaneous VNS (tVNS) Stroke Rehabilitation Therapy Medical Device Engineering Electrode Design and Prototyping Materials Science Biomedical Engineering Neurorehabilitation Clinical Usability Patient-Centred Design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-22 , Earliest start: 2024-11-24 , Latest end: 2025-10-31
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Medical and Health Sciences , Engineering and Technology
Better View Learning Using RL
Selecting the right viewpoint is crucial for effective perception and task execution in robotics and autonomous systems. Traditional rule-based methods often struggle in complex or dynamic settings. This project explores reinforcement learning (RL) to enable agents to autonomously learn adaptive viewpoint selection strategies. By maximizing task performance and information gain, the resulting policies aim to enhance system efficiency in applications such as active perception, autonomous exploration, and intelligent robotic control.
Keywords
Active Perception, Optimal Viewpoint Learning, Reinforcement Learning, Robotic Manipulation
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Published since: 2025-07-21 , Earliest start: 2025-07-28 , Latest end: 2026-04-30
Organization Robotic Systems Lab
Hosts Zurbrügg René , Bhardwaj Arjun
Topics Information, Computing and Communication Sciences , Engineering and Technology
Embedded algorithms of IMUs in a neurorehabilitation device
The goal of this project is to help develop embedded firmware for a imu based rehabilitation device. This project is part of the SmartVNS project which utilizes movement-gated control of vagus nerve stimulation for stroke rehabilitation.
Keywords
electrical engineering PCB Embedded systems neurorehabilitation
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Semester Project , Master Thesis
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Published since: 2025-07-17 , 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
Computational Modeling of Muscle Dynamics for Biohybrid Robots
This research aims to advance biohybrid robotics by integrating living biological components with artificial materials. The focus is on developing computational models for artificial muscle cells, a critical element in creating biohybrid robots. Challenges include modeling the complex and nonlinear nature of biological muscles, considering factors like elasticity and muscle fatigue, as well as accounting for fluid-structure interaction in the artificial muscle's environment. The research combines first principle soft body simulation methods and machine learning to improve understanding and control of biohybrid systems.
Keywords
Biohybrid Robotics, Computational Models, Soft Body Simulation, Finite Element Method (FEM), Muscle Dynamics, Soft Robotics
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-02-01 , Latest end: 2026-02-01
Organization Soft Robotics Lab
Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Biology , Physics
GPU Acceleration of Soft Robot Modeling: Enhancing Performance with CUDA
We are enhancing soft robot modeling by developing a GPU-accelerated version of our FEM-based framework using CUDA. This research focuses on optimizing parallel computations to significantly speed up simulations, enabling larger problem sizes and real-time control. By improving computational efficiency, we aim to advance soft robotics research and facilitate more detailed, dynamic simulations.
Keywords
Soft Body Simulation, high-performance computing, GPU programming, Parallel Computing, Finite Element Method (FEM), Multiphysics Simulation
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-07-11 , Earliest start: 2025-02-01 , Latest end: 2026-02-01
Organization Soft Robotics Lab
Hosts Katzschmann Robert, Prof. Dr. , Mekkattu Manuel
Topics Information, Computing and Communication Sciences , Engineering and Technology
Advancing Soft Robot Modeling: Integrating Physics, Optimization, and Control
We are advancing soft robot simulation with FEM and energy-based methods to model complex, adaptive behaviors. This research entails developing the framework to support diverse designs, integrate new physics models, and optimize performance, enabling enhanced control and real-world applications of soft robots.
Keywords
Soft Robotics, Finite Element Method (FEM), Physical Modeling, Benchmarking, Optimization, Multiphysics Simulation, Sim-to-Real
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Published since: 2025-07-11 , 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
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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Semester Project , Bachelor Thesis , Master Thesis
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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
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
Automatic Failure Detection for Drones
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: 2025-07-07 , Earliest start: 2025-02-01 , Latest end: 2026-01-31
Organization Robotics and Perception
Hosts Bauersfeld Leonard
Topics 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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Semester Project , Bachelor Thesis , Master Thesis
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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
Learning Robust Agile Flight via Adaptive Curriculum
This project focuses on developing robust reinforcement learning controllers for agile drone navigation using adaptive curricula. Commonly, these controllers are trained with a static, pre-defined curriculum. The goal is to develop a dynamic, adaptive curriculum that evolves online based on the agents' performance to increase the robustness of the controllers.
Keywords
Reinforcement Learning, Drones
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Semester Project , Master Thesis
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Published since: 2025-07-07 , Earliest start: 2023-11-01 , Latest end: 2024-12-31
Organization Robotics and Perception
Hosts Xing Jiaxu
Topics Engineering and Technology
Learning Rapid UAV Exploration with Foundation Models
Recent research has demonstrated significant success in integrating foundational models with robotic systems. In this project, we aim to investigate how these foundational models can enhance the vision-based navigation of UAVs. The drone will utilize learned semantic relationships from extensive world-scale data to actively explore and navigate through unfamiliar environments. While previous research primarily focused on ground-based robots, our project seeks to explore the potential of integrating foundational models with aerial robots to enhance agility and flexibility.
Keywords
Visual Navigation, Foundation Models, Drones
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Published since: 2025-07-07 , Earliest start: 2024-01-25 , Latest end: 2024-12-31
Organization Robotics and Perception
Hosts Xing Jiaxu
Topics Engineering and Technology
Energy-Efficient Path Planning for Autonomous Quadrotors in Inspection Tasks
Autonomous quadrotors are increasingly used in inspection tasks, where flight time is often limited by battery capacity. his project aims to explore and evaluate state-of-the-art path planning approaches that incorporate energy efficiency into trajectory optimization.
Keywords
Path Planning, Quadrotors
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Semester Project , Master Thesis
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Published since: 2025-07-07 , Earliest start: 2024-11-11 , Latest end: 2025-08-13
Organization Robotics and Perception
Hosts Bauersfeld Leonard
Topics Engineering and Technology
Event-based Particle Image Velocimetry
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: 2025-07-07 , 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
Volumetric Bioprinting of Engineered Muscle Tissues
We are working with an innovative volumetric printing technique – Xolography – to fabricate engineered muscle tissues that function as bioactuators for biohybrid systems. You will work at the interface between biology and robotics, helping us exploring new designs and strategies to advance the field of muscle tissue engineering and muscle-powered living machines.
Keywords
bioprinting, muscle, tissue engineering, 3D cell culture, hydrogels, biohybrid robotics, regenerative medicine, 3D models, biomaterials, biofabrication.
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-06-27 , Earliest start: 2025-07-15
Organization Soft Robotics Lab
Hosts Badolato Asia
Topics Medical and Health Sciences , Engineering and Technology , Chemistry , Biology
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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Semester Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , Summer School
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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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Semester Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , Summer School
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Published since: 2025-06-23
Organization Rehabilitation Engineering Lab
Hosts Viskaitis Paulius
Topics Information, Computing and Communication Sciences
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. , Paez Diego, Dr.
Topics Engineering and Technology