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 C++ 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
| 746 – Developing a fluid-body simulator to study collective behavior in water |
| Category: | semester project, master project (full-time) | |
| Keywords: | C++, Python, Simulator | |
| Type: | 20% theory, 80% software | |
| Responsible: | (MED 1 1024, phone: 30563) | |
| Description: | Efficient swimmers rely on sensing the local changes in surrounding waters and use them to their advantage. For example, fishes swimming in water can sense local deformations generated by the vortices generate by surrounding fishes and swim in school formations to reduce the energetic cost. What are the key components of these behaviors? In this project, you will study this problem in simulation. Previous simulations of movement of body in fluid consider overly simplified fluid models, that does not capture the fluid dynamics, or simplified body models. We recently developed a new fluid-body simulator that can simulate the dynamics of complex rigid body geometries, similar to that of a real fishes and robots, and the dynamics of the fluid. This allows the study of collective behaviors like schooling and the incorporation of water sensing. The main goal of this project is to continue the development of the fluid solver in PyTorch, and test the ability of the model to generate self-propelled swimming. The goals can be divided in four subgoals (in order of priority): 1. Implement an interpolation method for the body fitted meshes to compute the velocities of the bodies in the fluid solver. 2. Improve the simulator's performance by porting part of the fluid solver in C++/CUDA by writing a PyTorch extension. 3. Validate the solver based on traditional benchmark tests and particle image velocimetry data from a swimming robot, and against simpler drag based fluid models. 4. Test and refine the implementation of the forces acting from the fluid to the body. Last edited: 15/11/2024 | |
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, 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, (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: 05/11/2024 | |
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 | |
Mobile robotics
| 651 – Autonomous Drifting on Scaled Vehicle Hardware |
| Category: | semester project, master project (full-time), internship | |
| Keywords: | C++, Control, Electronics, Embedded Systems, Experiments, Learning, Optimization | |
| Type: | 10% theory, 60% hardware, 30% software | |
| Responsible: | (MED 1 1024, phone: 37506) | |
| Description: | Controlling vehicles at their limits of handling has significant implications from both safety and autonomous racing perspectives. For example, in icy conditions, skidding may occur unintentionally, making it desirable to safely control the vehicle back to its nominal working conditions. From a racing perspective, drivers of rally cars drift around turns while maintaining high speeds on loose gravel or dirt tracks. In this project, the student will compare several approaches for high speed, dynamic vehicle maneuvers, including NMPC with a standard dynamic bicycle model, NMPC with a dynamic bicycle model + GP residuals, NMPC with learned dynamics (i.e. a NN), and lastly a pure model-free reinforcement learning approach. All approaches will be tested in both simulation as well as on a scaled vehicle hardware platform. 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.