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    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.

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    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

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