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 Programming 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
| 736 – Firmware development for a sensorized Pleurobot |
| Category: | semester project, master project (full-time) | |
| Keywords: | C, C++, Communication, Control, Embedded Systems, Firmware, Linux, Programming, sensor | |
| Type: | 5% theory, 10% hardware, 85% software | |
| Responsible: | (MED 1 1626, phone: 38676) | |
| Description: | In this project, the student is expected to continue developing the existing firmware for high-performance low-level control of the new Pleurobot (our amphibious legged robot modeling Pleurodeles waltl) and its multiple sensors. The major objectives include: (1) Improve the sampling speed and robustness of the microcontrollers that collect data from multiple sensors. (2) Increase the bandwidth of and reduce the latency in the communication between the onboard computer and multiple microcontrollers. (3) (For full-time students) Develop low-latency wireless communication between the onboard computer and the user's laptop for remote control. The student is expected to be familiar with (1) communication protocols including SPI, UART, and CAN, and (2) programming of embedded systems using C/C++. Knowledge about signal processing, wireless network protocols, and/or GUI development can be a bonus. The student who is interested in this project could send his/her transcript, CV, and description of their past project experience to qiyuan.fu@epfl.ch. A student who can work full-time in the summer or the autumn semester is preferred. Last edited: 16/05/2024 | |
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 | |
Miscellaneous
| 742 – Create synthetic salamander dataset with domain randomization and unsupervised generative attentional networks |
| Category: | semester project, master project (full-time) | |
| Keywords: | 3D, C++, Computer Science, Data Processing, Machine learning, Programming, Vision | |
| Type: | 20% theory, 80% software | |
| Responsible: | (MED 1 1611, phone: 36620) | |
| Description: | Powerful deep-learning based tracking method for animal behaviors requires large-scale curated and annotated data. Several recent papers [1,2] revealed the possibility to leverage the data requirement by rendering animated synthetic animals such as mice and ants. In this project, the student will work on an existing biomechanical model of Salamander Pleurodeles Waltl to create a synthetic dataset for marklerless keypoint tracking tasks. The dataset would help improve the performance of a salamander tracking network, which would ultimately provide invaluable kinematics data for designing muscle models, neural controllers and validating neuroscience hypothesis. For a PdM, this project involves:
For a semester project, work packages will be optionally dropped and tailored according to student’s skills and interests. The student is expected to have good programming skills and previous experience/knowledge in deep learning. Knowledge in 3D modeling and computer graphics is a plus but not required. If interested, please send an email to Chuanfang Ning with your motivation, CV, transcripts and most relevant experience. [1] Bolaños, Luis A., et al. "A three-dimensional virtual mouse generates synthetic training data for behavioral analysis." [2] Plum, Fabian, et al. "replicAnt: a pipeline for generating annotated images of animals in complex environments using Unreal Engine." [3] Kim, Junho, et al. "U-gat-it: Unsupervised generative attentional networks with adaptive layer-instance normalization for image-to-image translation." [4] Mathis, Alexander, et al. "DeepLabCut: markerless pose estimation of user-defined body parts with deep learning." Last edited: 27/06/2024 | |
4 projects found.