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 Computer Science 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

767 – Data collection pipeline for sensorized amphibious robot experiments
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Category:semester project, master project (full-time)
Keywords:3D, C, C++, Communication, Computer Science, Data Processing, Experiments, Firmware, Image Processing, Motion Capture, Programming, Python, Robotics, Synchronization, Vision
Type:5% theory, 20% hardware, 75% software
Responsible: (MED 1 1626, phone: 38676)
Description:

This project has been taken

In this project, the student will work closely with the other team members to develop data collection pipelines during the experiments of a sensorized amphibious robot and, optionally, use them to collect and analyze experimental data. Specifically, the student needs to:

  • Build a multi-camera system for tracking 3-D kinematics of the robots, ideally in real time. The system is expected to work in both indoor and outdoor experiments. We already have a few working setups, and the student needs to replicate them using new hardware, calibrate the system, and implement real-time tracking nodes in ROS2.
  • Synchronize data collected from multiple resources: cameras, force sensors, motors, etc.
  • Visualize the data collected in Mujoco viewer, RViz, Blender, or other 3D visualizers.
  • Help collect experimental data.
  • (For master project only) Help analyze data or use learning algorithms to find underlying patterns.

The student is expected to be familiar with programming in C/C++ and Python, using ROS2, and robot kinematics. Experience with Docker, Linux kernel, communication protocols, and computer vision algorithms would be a bonus.

The student who is interested in this project shall send the following materials to the assistant: (1) resume, (2) transcript showing relevant courses and grades, and (3) other materials that can demonstrate their skills and project experience (such as videos, slides, code repositories, etc.).



Last edited: 17/01/2026

Mobile robotics

768 – Aria2Robot: Egocentric data-driven policy learning for robot manipualtion
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Category:semester project, master project (full-time), internship
Keywords:Computer Science, Machine learning, Programming, Python, Robotics, Vision
Type:30% theory, 10% hardware, 60% software
Responsibles: (undefined, phone: 37432)
(MED11626, phone: 41783141830)
Description:INTRODUCTION Egocentric wearable sensing is becoming a key enabler for embodied AI and robotics. Meta’s Project Aria (https://www.projectaria.com/) research glasses provide rich, multimodal, first-person observations (RGB video, scene cameras, IMUs, microphones, eye-tracking, and more) in a socially acceptable, all-day wearable form factor, specifically designed to advance egocentric AI, robotics, and contextual perception research. In collaboration with Meta, we aim to tightly couple Aria research glasses with our existing manipulation platforms at EPFL. This project will 1] Integrate the Aria Research Kit (Aria Gen 2) with our ROS2-based robot platforms (ViperX 300S and WidowX-250 arms on a mobile base), including calibration and time-synchronisation with RGB-D cameras and robot state; 2] Design and execute egocentric data collection in household-like environments (Aria + RealSense + robot joint trajectories + language annotations); 3] Develop egocentric data-driven policies for robotic manipulation through learning from demonstration. (Robot can be a robot arm or a humanoid robot (Reaman)) 4] Explore one or more robotics applications powered by Aria signals, such as intention-aware teleoperation, egocentric demonstrations for policy learning, or vision-language(-action) fine-tuning for assistance tasks; and 5) Perform systematic platform testing, validation, and documentation to deliver a reusable research pipeline for future projects. Excellent programming skills (Python) are a plus. IMPORTANCE: We have well-documented tutorials on using the robots, teleoperation interfaces for data collection, using the HPC cluster, and a complete pipeline for training robot policies. The Aria Research Kit and tools (recording, calibration, dataset tooling, SDK) will be integrated into this ecosystem, so the student can focus on the research questions rather than low-level setup. We already have a good base and results based on the ongoing project. What makes Aria special for robotics? Project Aria glasses are multi-sensor “research smart glasses”: multiple cameras (wide FOV), IMUs, microphones, eye gaze, and a Machine Perception Service (MPS) that provides SLAM poses, hand poses, etc. They’re explicitly marketed by Meta as a research kit for contextual AI and robotics – i.e., using egocentric sensing to build embodied agents that understand and act in the world. Compared to a normal RGB-D camera, Aria gives you: Egocentric view: “what the human (or robot) sees” while acting. Calibrated head pose/trajectory (via SLAM in MPS). Hand/gaze info (depending on what parts you use). A portable, wearable, socially acceptable form factor. WHAT WE HAVE: [1] Ready-and-easy-to-use robot platforms: including ViperX 300S and WidowX-250 arms, configured with 4 RealSense D405 cameras, various grippers, and a mobile robot platform. [2] Egocentric sensing hardware: Meta Project Aria research glasses (Aria Gen 2), including access to the Aria Research Kit and tooling for data recording and processing. [3] Computing resources: TWO desktop PCs with NVIDIA GPUs 5090 and 4090. Interested students can apply by emailing sichao.liu@epfl.ch or lixuan.tang@epfl.ch. Please attach your transcript and a short description of your past/current experience on related topics (robotics, computer vision, machine learning, AR/egocentric perception). The position is open until we have final candidates. Otherwise, the position will be closed. Recommend to read: [1] Kareer, Simar, et al. "Egomimic: Scaling imitation learning via egocentric video." 2025 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2025. [2] Liu, Vincent, et al. "Egozero: Robot learning from smart glasses." arXiv preprint arXiv:2505.20290 (2025). [3] Punamiya, Ryan, et al. "EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World." arXiv preprint arXiv:2604.07607 (2026). [4] Saroha, Abhishek, et al. "EgoFlow: Gradient-Guided Flow Matching for Egocentric 6DoF Object Motion Generation." arXiv preprint arXiv:2604.01421 (2026). [5] Zheng, Ruijie, et al. "Egoscale: Scaling dexterous manipulation with diverse egocentric human data." arXiv preprint arXiv:2602.16710 (2026). [6] Aria project: https://www.projectaria.com/resources/ [7] Aria GitHub: https://github.com/facebookresearch/projectaria_tools

Last edited: 22/04/2026

2 projects found.