Biorobotics Laboratory BioRob
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. 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 Robotics 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
| 741 – Development of a series elastic actuator with torque/force control |
| Category: | semester project, master project (full-time) | |
| Keywords: | Compliance, Control, Embedded Systems, Prototyping, Robotics | |
| Type: | 20% theory, 60% hardware, 20% software | |
| Responsible: | (MED 1 1626, phone: 38676) | |
| Description: | This project aims to continue the development of a series elastic actuator (SEA) for a salamander robot. Despite the availability of various off-the-shelf servo motors, it is difficult to find one that can provide accurate torque/force control to validate advanced control methods involving musculoskeletal models, provide large torque output, and be compact in size. SEAs are promising in satisfying these requirements, see this paper as an example: http://biorobotics.ri.cmu.edu/papers/paperUploads/DSCC2013-3875.pdf A preliminary design of the geared motor that will drive the elastic component has been completed. This project will mainly focus on the design and manufacturing of the elastic component, the programming of the electronics, and the design of the feedback controller. Multiple iterations of testing and improvement will be needed, so the student is expected to have great time management skills. If there is sufficient time, the following topics can be explored: (1) Modify the design to test hypotheses about multiarticular muscles. (2) Integrate the motor to a salamander robot and test various scientific hypotheses. (3) Waterproofing the motor module for amphibious applications. Students with a solid background in mechanical design and control theory are preferred. Interested students could send CVs, transcripts, materials that can demonstrate project experience (videos, slides, reports, etc.), if possible, and several potential time slots for a quick meeting to qiyuan.fu@epfl.ch. Last edited: 24/06/2024 | |
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, 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 your CV, previous experiences that could be relevant to the project, and what interests you the most about this research topic (to be discussed during the interview). Last edited: 19/04/2024 | |
Quadruped robotics
A small excerpt of possible projects is listed here. Highly interested students may also propose projects, or continue an existing topic.
| 743 – Quadruped Robot Projects (Several) |
| Category: | semester project, master project (full-time) | |
| Keywords: | Agility, Artificial muscles, Bio-inspiration, C++, Computer Science, Control, Experiments, Learning, Locomotion, Machine learning, Muscle modeling, Online Optimization, Optimization, Programming, Python, Quadruped Locomotion, Robotics, Simulator, Vision | |
| Type: | 10% theory, 20% hardware, 70% software | |
| Responsible: | (MED 1 1024, phone: 37506) | |
| Description: | There are several quadruped robot projects available related to locomotion, jumping, and human-robot interaction, with methodologies including deep reinforcement learning, imitation learning, optimal control, and computer vision. Students who already have experience with deep learning, C++, vision, and who have worked with hardware are especially encouraged to apply. Please send Guillaume your CV, transcript, and explain your motivation on what kind of topics you would be interested in working on (more details = better!). Last edited: 18/07/2024 | |
| 652 – Integrating Learning-Based Control with MPC and CPGs |
| Category: | semester project, master project (full-time), internship | |
| Keywords: | Bio-inspiration, Control, Learning, Locomotion, Optimization, Robotics | |
| Type: | 40% theory, 60% software | |
| Responsible: | (MED 1 1024, phone: 37506) | |
| Description: | Recent years have shown impressive locomotion control of dynamic systems through a variety of methods, for example with optimal control (MPC), machine learning (deep reinforcement learning), and bio-inspired approaches (CPGs). Given a system for which two or more of these methods exist: how should we choose which to use at run time? Should this depend on environmental factors, i.e. the expected value of a given state? Can this help with explainability of what exactly our deep reinforcement learning policy has learned? In this project, the student will use machine learning to answer these questions, as well as integrate CPGs and MPC into the deep reinforcement learning framework. The methods will be validated on systems including quadrupeds and model cars first in simulation, with the goal of transferring the method to hardware. To apply, please email Guillaume with your motivation, CV, and briefly describe your relevant experience (i.e. with machine learning, software engineering, etc.). Last edited: 09/01/2024 (revalidated 18/07/2024) | |
4 projects found.