Project Database
This page contains the database of possible research projects for master and bachelor students in the Biorobotics Laboratory (BioRob). Visiting students are also welcome to join BioRob, but it should be noted that no funding is offered for those projects (see https://biorob.epfl.ch/students/ for instructions). To enroll for a project, please directly contact one of the assistants (directly in his/her office, by phone or by mail). Spontaneous propositions for projects are also welcome, if they are related to the research topics of BioRob, see the BioRob Research pages and the results of previous student projects.
Search filter: only projects matching the keyword Data Processing are shown here. Remove filter
Amphibious robotics
Computational Neuroscience
Dynamical systems
Human-exoskeleton dynamics and control
Humanoid robotics
Miscellaneous
Mobile robotics
Modular robotics
Neuro-muscular modelling
Quadruped robotics
Amphibious robotics
| 753 – Gait analysis in the salamander from pose estimation |
| Category: | semester project | |
| Keywords: | Data Evaluation, Data Processing | |
| Type: | 100% software | |
| Responsible: | (MED 1 1024, phone: 30563) | |
| Description: | The project will involve the analysis of the kinematics tracking of key poses on salamanders in land and water before and after spinal cord injury in python. The goal of the project is to analyze the data using signal processing tools, eliminate undesired samples, and use classification tools to determine each gait at different stages before and after spinal cord injury. Last edited: 27/02/2025 | |
Computational Neuroscience
| 755 – High-performance enconder-decoder design for computational neural signal processing |
| Category: | semester project, master project (full-time), internship | |
| Keywords: | Computational Neuroscience, Data Processing, Linux, Programming, Python | |
| Type: | 20% theory, 5% hardware, 75% software | |
| Responsible: | (MED11626, phone: 41783141830) | |
| Description: | Background Brain-computer interfaces (BCIs) using signals acquired with intracortical implants have achieved successful high-dimensional robotic device control useful for completing daily tasks. However, the substantial amount of medical and surgical expertise required to correctly implant and operate these systems greatly limits their use beyond a few clinical cases. A non-invasive counterpart requiring less intervention that can provide high-quality control would profoundly improve the integration of BCIS into multiple settings, and represent a nascent research field, brain robotics. However, this is challenging due to the inherent complexity of neural signals and difficulties in online neural decoding with efficient algorithms. Moreover, brain signals created by an external stimulus (e.g., vision) are most widely used in BCI-based applications, but it is impractical and infeasible in dynamic yet constrained environments. A question arises here: "How to circumvent constraints associated with stimulus-based signals? Is it feasible to apply non-invasive BCIS to read brain signals, and how to do so?". To a step further, I wonder could it be possible to accurately decode complete semantic-based command phrases in real time, and further achieve seamless and natural brain-robot systems for control and interactions? The project is for a team of 1-2 Master's students, and breakdown tasks will be assigned to each student later according to their skill set. What needs to be implemented and delivered at the end of the project? 1) A method package of brain signal pre-processing and feature formulation 2) An algorithm package of an encoder and a decoder of neural signals. 3) A model of training brain signals with spatial and temporal features. Last edited: 13/05/2025 | |
Human-exoskeleton dynamics and control
| 735 – Hip exoskeleton to assist walking - multiple projects |
| Category: | semester project, master project (full-time), bachelor semester project, internship | |
| Keywords: | Bio-inspiration, C, C++, Communication, Compliance, Control, Data Processing, Dynamics Model, Electronics, Experiments, Inverse Dynamics, Kinematics Model, Learning, Locomotion, Machine learning, Online Optimization, Optimization, Programming, Python, Robotics, Treadmill | |
| Type: | 30% theory, 35% hardware, 35% software | |
| Responsible: | (MED 3 1015, phone: 31153) | |
| Description: | Exoskeletons have experienced an unprecedented growth in recent years and hip-targeting active devices have demonstrated their potential in assisting walking activities. Portable exoskeletons are designed to provide assistive torques while taking off the added weight, with the overall goal of increasing the endurance, reducing the energetic expenditure and increase the performance during walking. The design of exoskeletons involves the development of the sensing, the actuation, the control, and the human-robot interface. In our lab, a hip-joint active hip orthosis (“eWalk”) has been prototyped and tested in recent years. Currently, multiple projects are available to address open research questions. Does the exoskeleton reduce the effort while walking? How can we model human-exoskeleton interaction? How can we design effective controls? How can we optimize the interfaces and the control? Which movements can we assist with exoskeletons? To address these challenges, the field necessitates knowledge in biology, mechanics, electronics, physiology, informatics (programming, learning algorithms), and human-robot interaction. If you are interested in collaborating in one of these topics, please send an email to giulia.ramella@epfl.ch with (1) your CV+transcripts, (2) your previous experiences that could be relevant to the project, and (3) what interests you the most about this research topic (to be discussed during the interview). Last edited: 22/01/2025 | |
3 projects found.