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 Data Processing 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
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 |
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 |
2 projects found.