 Institute of Robotics and Intelligent Systems D-MAVTOpen OpportunitiesJoin a team of scientists improving the long-term prognosis and treatment of Spinal Cord Injury (SCI) through mobile and wearable systems and personalized health monitoring.
Joining the SCAI Lab part of the Sensory-Motor Systems Lab at ETH, you will have the unique opportunity of working at one of the largest and most prestigious health providers in Switzerland: Swiss Paraplegic Center (SPZ) in Nottwil (LU). - Artificial Intelligence and Signal and Image Processing, Computer Software, Data Format, Information Systems
- ETH Zurich (ETHZ), Internship, Lab Practice, Student Assistant / HiWi
| The uprise of consumer-grade fitness trackers has opened the doors to long-term activity monitoring in the wild in research and clinics. However, Fitbit does not identify napping episodes shorter than 90 minutes. Hence, there is a need to establish a robust algorithm to detect naps. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Biosensor Technologies, Electrical and Electronic Engineering
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis
| 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. - Engineering and Technology, Information, Computing and Communication Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| The ability to manipulate micro-scale objects with precision is a growing field in biomedical engineering, particularly in the context of treating thrombotic conditions. Thrombolysis, the process of dissolving blood clots, remains a significant challenge in medical treatment, with current techniques often limited by their invasiveness and effectiveness. Recent advancements have explored the use of microrobots for targeted thrombolysis, leveraging their ability to maneuver in complex biological environments to enhance clot dissolution and drug delivery. Rotation plays a crucial role in various natural processes, including feeding and locomotion, demonstrating its effectiveness in achieving complex interactions with the environment. However, achieving ultrafast rotation in artificial microrobots presents significant engineering challenges. Traditional methods of inducing rotation, such as acoustic manipulation, have shown promise but are often constrained by limitations in rotational speed and control precision. These constraints hinder the microrobot's ability to effectively engage with functions.
In response to these challenges, we introduce an innovative solution: an untethered ultrafast-rotating spiral microrobot designed for physical thrombolysis. This microrobot employs a symmetric spiral structure that generates a consistent torque while maintaining a zero net force, allowing for sustained high-speed rotation. The unique design of the spiral structure ensures efficient rotational motion, overcoming previous limitations in rotation speed. A key feature of our microrobot is its sharp-tip design, which enhances its ability to penetrate and mechanically disrupt thrombi. This mechanical drilling action facilitates the breakdown of clots, making thrombolysis more effective. Additionally, the microrobot incorporates a drug-holding cavity, enabling it to deliver therapeutic agents directly to the site of the thrombus. This dual functionality—mechanical disruption combined with targeted drug delivery—promises a more efficient approach to thrombolysis. This ultrafast-rotating microrobot represents a significant advancement in microrobot design and its application in medical treatments.
- Engineering and Technology
- Master Thesis
| 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.
- Engineering and Technology
- Master Thesis
| 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. - Biological Mathematics, Biomechanical Engineering, Biophysics, Mechanical Engineering, Modeling and Simulation, Robotics and Mechatronics, Simulation and Modelling
- Bachelor Thesis, Master Thesis, Semester Project
| 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. - Mechanical Engineering, Programming Techniques, Robotics and Mechatronics, Simulation and Modelling
- Bachelor Thesis, Master Thesis, Semester Project
| 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. - Mechanical Engineering, Robotics and Mechatronics, Simulation and Modelling
- Bachelor Thesis, Master Thesis, Semester Project
| 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. - Intelligent Robotics
- Master Thesis, Semester Project
| 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.
- Intelligent Robotics, Robotics and Mechatronics
- Master Thesis, Semester Project
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