 Institute of Robotics and Intelligent Systems D-MAVTOpen OpportunitiesIn this project, we first perform the rotation manipulation of zebrafish using an acoustically actuated capillary. Then, we would like to realize the precise 3D reconstruction of the in vivo organs of live zebrafish larvae using CV and AI algorithms. We will fabricate a microchannel chip, which can develop a single polarized vortex. By adjusting the acoustic excitation parameters, we will change the rotational speed and direction. Finally, we will program our only 3D reconstruction algorithms and software. - Acoustics and Acoustical Devices; Waves, Microbiology, Programming Languages, Robotics and Mechatronics
- Bachelor Thesis, Master Thesis, Semester Project
| Modern robots collect data from various sensors. When these sensors operate independently, time-synchronization through rectification of their individual clocks and correction for temporal drift is required.
In our previous work, we developed an initial version of a synchronization pipeline in Python, designed for offline data synchronization. Our current pipeline already effectively synchronizes sensors that include a common external synchronization signal. Despite already working well, our current pipeline still requires some expertise to configure the data sources. To make the pipeline widely usable, we now need to make it function seamlessly even without expert knowledge and access to external synchronization signals. This enhancement should also extend to scenarios involving continuous online data as well.
Furthermore, we want to prove the correctness of the synchronization and showcase the performance based on synthetic data.
In essence, your thesis will comprise the following key objectives:
1. Understand the challenges involved in data synchronization.
2. Familiarize yourself with the existing synchronization pipeline.
3. Innovate strategies for achieving data synchronization without relying on external synchronization signals.
4. Enhance the user interface by creating an intuitive guide for using the pipeline effectively.
5. Extend the functionality to accommodate online data streams.
6. Assess the pipeline's correctness and performance using synthetic biosignals, as well as pre-recorded biosignals from the SMS-Lab and Tohoku University.
Throughout this project, you will receive guidance from me, a 4th year PhD candidate at the Sensory-Motor Systems Lab at ETH Zurich, and researchers at Tohoku University in Sendai, Japan. As I will be in Japan from October, we will conduct the weekly meetings over Zoom.
Furthermore, in case of interest, you have the exciting opportunity to visit us in Japan. This opportunity can be pursued either through personal funding or by applying for respective scholarships, such as the Heyning-Roelli Foundation, SEMP, Spickenreuther Foundation, and others. I have received scholarships in the past and I am happy to provide guidance and support throughout the application process. - Biosensor Technologies, Data Storage Representations, Data Structures, Digital Systems, Information Storage, Retrieval and Management, Pattern Recognition, Signal Processing, Simulation and Modelling, Software Engineering
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| In this project, we focus on continuous and quantitative monitoring of activities of daily living (ADL) in SCI individuals with the goal of identifying cardiovascular events and PI-related risk behaviors.
ADLs specific to SCI patients and their lifestyles shall be discussed and narrowed down in the scope of this work, therefore an autonomous camera-based system is proposed to classify ADLs.
The Current work builds on a previous project where a SlowFast network [1] was trained to identify SCI-specific classes and we aim to further improve the classification and temporal resolution for transferring to wearables' time-series data. - Computer Vision, Health Information Systems (incl. Surveillance), Intelligent Robotics, Knowledge Representation and Machine Learning, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, MD
| Robots need to manipulate a wide range of unknown objects, from transparent to shiny surfaces. The goal of this project is to investigate learning techniques to bridge the visual domain gap between high-fidelity rendered scenes and real-world images for scene understanding.
- Computer Vision, Intelligent Robotics, Knowledge Representation and Machine Learning
- Master Thesis
| One of the new disciplines at the upcoming CYBATHLON is the vision assistance race. Visual impaired people are severely limited in their autonomy of completing many daily tasks. Available vision aids are limited to specific domains, such as reading text out loud, but fail to generalize. Smart vision assistive technologies could provide more intuitive, comprehensive and reliable support in daily tasks.
The CYBATHLON challenges contain a variety of daily situations, such as shopping, finding a free seat or ringing the correct doorbell. The goal is to develop an assistive device capable of fulfilling all challenges.
- Computer Vision, Image Processing, Intelligent Robotics, Mechanical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic
- Semester Project
| Diffusion models have a huge potential in motion planning and navigation. In this project, we focus on generating spline-based trajectories using diffusion models able to make ANYmal navigate in extremely challenging dynamic environments - Intelligent Robotics
- Master Thesis, Semester Project
| Together with the Schulthess Clinic, the Sensory-Motor Systems Lab, ETH Zurich, has developed the mHIRex which, based on the common clinical manoeuvre, precisely determines the force required for internal hip rotation. The next step would be to assess hip internal rotation in a large cohort of consecutive patients with hip disorders. - Biomechanics, Clinical Engineering, Clinical Sciences, Sports Medicine
- Internship, Master Thesis
| 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 develop a generalist digging agent that is able to do multiple tasks, such as digging and moving loose soil, using our legged excavator. We plan to use decision transformers, trained on offline data, to accomplish these tasks - Intelligent Robotics
- Master Thesis, Semester Project
| In this work we would utilize reinforcement learning, neural network actuator modeling, and perception for the control and arm motion planning of a 75ton excavator with a free-swinging joint.
The project will be in collaboration with LIEBHERR, a german company building excavators and other construction machines. - Computer Vision, Intelligent Robotics, Mechanical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Systems Theory and Control
- CLS Student Project (MPG ETH CLS), Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis, Other specific labels, Semester Project
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