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 Learning 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
Human-exoskeleton dynamics and control
| 735 – Hip exoskeleton to assist daily activities |
| Category: | semester project, master project (full-time), internship | |
| Keywords: | Bio-inspiration, C, C++, Communication, Compliance, Control, Data Processing, Dynamics Model, Electronics, Embedded Systems, 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 portable active devices have demonstrated their potential in assisting locomotion activities, increasing endurance, and reducing the walking effort. In our lab, a hip active orthosis (“eWalk”) has been prototyped and tested in recent years. Some projects will be available to address open research questions revolving around the topics of control, experimental evaluations, sensing, and embedded systems optimization. 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). Please send the email from your institutional account, and include the type of project and in which semester you are interested in doing the collaboration. Last edited: 17/11/2025 | |
Quadruped robotics
A small excerpt of possible projects is listed here. Highly interested students may also propose projects, or continue an existing topic.
| 769 – Learning Morphology-Specific Emergence of Gaits |
| Category: | master project (full-time) | |
| Keywords: | Biomimicry, Computational Neuroscience, Learning, Python, Simulator | |
| Type: | 20% theory, 80% software | |
| Responsible: | (MED 1 1226, phone: 32658) | |
| Description: | Why do horses and and camels both walk at slow speeds and gallop at fast speeds, but at intermediate speeds horses prefer to trot while camels pace? While gait transitions have been well studied for a given morphology, these models rarely explain when and why animals prefer different or gaits despite being quite similar, or the same gaits despite having very different morphologies. This project tackles this question through the lens of reinforcement learning (RL), with a focus on the role of entrainment between an internal oscillator model and the mechanical dynamics, i.e the morphology. You will explore both top-down and bottom-up coupling mechanisms, unconventional reward functions such as viability measures, and benchmark these approaches across different morphological parameters (e.g length-to-height and width-to-height ratios, mass). Stretch goals can include evaluating the role of active exploration in a hierarchical RL setup, exploring sprawling or bipedal morphologies, changing morphology during learning (e.g. growth), or you may propose something in discussion with the supervisors. NOTE: this is a collaboration project, to be conducted at Cornell University, USA. | |
Mobile robotics
| 754 – Vision-language model-based mobile robotic manipulation |
| Category: | semester project, master project (full-time), internship | |
| Keywords: | Control, Experiments, Learning, Python, Robotics, Vision | |
| Type: | 30% theory, 10% hardware, 60% software | |
| Responsible: | (MED11626, phone: 41783141830) | |
| Description: | INTRODUCTION Recent vision-language-action models (VLAs) build upon pre-trained vision-language models and leverage diverse robot datasets to demonstrate strong task execution, language-following ability, and semantic generalisation. Despite these successes, VLAs struggle with novel robot setups and require fine-tuning to achieve good performance; however, the most effective way to fine-tune them is unclear, given the numerous possible strategies. This project aims to 1) develop a customised mobile robot platform that is composed of a customised and ROS2-based mobile base and robot arms with 6DOF (ViperX 300 S and Widowx 250), and 2) establish a vision system equipped with RGBD cameras which is used for data collection, 3) deploy a pre-trained VLA model locally for robot manipulation by using reinforcemnet and imittaion learning, with a focus of household environment, and 4) platform testing, validation and delivery. Excellent programming skill (Python) is a plus. Importance: We have well-documented tutorials of how to use robots, teleoperation for data collection, how to use the HPC cluster, and a complete pipeline to train robot policy. For applicants not from EPFL, to obtain the student status at EPFL, the following conditions must be fulfilled (an attestation has to be provided during the online registration): [1] To be registered at a university for the whole duration of the project [2] The project must be required in the academic program and recognised by the home university [3] The duration of the project is a minimum of 2 months and a maximum of 12 months [4] To be accepted by an EPFL professor to do a project under his supervision For an internship, six months at least is suggested. WHAT WE HAVE: [1] Ready-and-easy-to-use robot platforms: including ViperX 300S and WidowX-250, configured with 4 RealSense D405, various grippers, and mobile robot platform [2] Computing resources: TWO desktop PC with NVIDIA GPU 5090 and 4090 [3] HPC cluster with 1000h/month on NVIDIA A100 and A100fat : can use 1000 hours of A100 and A100 fat NVIDIA GPU every month, supports large-scale training and fine-tuning. Interested students can apply by sending an email to sichao.liu@epfl.ch. Please attach your transcript and past/current experience on the related topics. The position is open until we have final candidates. Otherwise, the position will be closed. Recommend to read: [1] LeRobot: Making AI for Robotics more accessible with end-to-end learning, https://github.com/huggingface/lerobot [2] Kim, Moo Jin, Chelsea Finn, and Percy Liang. "Fine-tuning vision-language-action models: Optimizing speed and success." arXiv preprint arXiv:2502.19645 (2025). [3] https://docs.trossenrobotics.com/aloha_docs/2.0/specifications.html [4] Lee BK, Hachiuma R, Ro YM, Wang YC, Wu YH. Unified Reinforcement and Imitation Learning for Vision-Language Models. arXiv preprint arXiv:2510.19307. 2025 Oct 22. Benchmark: [1] LeRobot: Making AI for Robotics more accessible with end-to-end learning [2] DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset [3] DiT-Block Policy: The Ingredients for Robotic Diffusion Transformers [4] Open X-Embodiment: Robotic Learning Datasets and RT-X Models Please come to office MED01612 Last edited: 11/12/2025 | |
3 projects found.