 Institute of Robotics and Intelligent Systems D-HESTOpen OpportunitiesYou will obtain functional constructs of living muscle tissue that can be implemented into robots as bio-actuators. The tissue will be realized via bioprinting or conventional biofabrication in 3D designs at the mm-to-cm scale. The deformation of the constructs will be achieved via electrical stimulation of contractile muscle cells, and integrated sensing elements will monitor the motion of the tissue constructs, improving functionality and autonomy. - Biology, Engineering and Technology, Medical and Health Sciences
- Master Thesis, Semester Project
| The goal of the project is to develop a simple and versatile method for production of robust conductive patterns on textile via deposition of conductive polymers. This technology will allow further development of wearable electronics for biomedical applications. - Chemistry, Medical and Health Sciences, Polymers
- Bachelor Thesis, Semester Project
| The goal of the project is to modify commercially available conductive yarns to improve their operational properties for potential employment in novel garment-embedded sensors for human motion detection. - Engineering and Technology, Medical and Health Sciences, Other Chemistry
- Semester Project
| The project is devoted to development of new generation sensors for human bodily fluid biomarkers. The main aim is development of compact and non-invasive modified electrodes for electrochemical sensing of these important compounds. - Analytical Chemistry, Biosensor Technologies, Electrochemistry, Medical and Health Sciences
- Master Thesis
| It was recently shown that helical auxetic structure allows one to achieve strain sensitive fibres with high sensitivity. Rigidity/stiffness of components of these sensors also plays a role in sensitivity to strain. To further improve our recently published textile strain sensing modality—helical auxetic yarn capacitive sensors—we are seeking a thesis/project student to develop a conductive composite formulation and process to wet-spin fibres of different stiffnesses. Employed as sensors, the effect of stiffness on sensitivity can be tested experimentally. The outcome of this project will further the development of highly sensitive, scalable textile strain sensors. - Biomedical Engineering, Chemistry, Composite Materials, Polymers, Process Control and Simulation
- Master Thesis, Semester Project
| A new platform is to be developed that can be used to promote the training of wake-initiated lucid dreaming and can also be used to apply mental relaxation strategies. - Biomedical Engineering, Electrical and Electronic Engineering, Interdisciplinary Engineering, Mechanical and Industrial Engineering
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| This project aims to develop and validate an easy-to-use, versatile and cloud Virtual Reality (VR) platform, combining customizable visual scenarios and Transcutaneous Electrical Nerve Stimulation (TENS), for the assessment and intervention of disabilities leading to body representation disorders. On one hand, the system holds potential to gather closer insights on how patients perceive their body due to their condition. On the other hand, the platform would exploit VR features to create personalized and interactive scenarios for rehabilitation purposes. - Biomedical Engineering, Information, Computing and Communication Sciences, Medical and Health Sciences
- Internship, Master Thesis, Semester Project
| This project aims to develop a clinically usable electrode for transcutaneous vagus nerve stimulation (tVNS) therapy. The objective is to create an electrode that is biocompatible, low-impedance, and easy to use, allowing patients to apply it themselves with minimal setup time. The project involves conducting a literature review, evaluating existing designs, selecting appropriate materials, developing a prototype, and assessing its efficacy and usability in a clinical setting. The outcome will be an electrode that enhances the convenience and effectiveness of tVNS therapy, contributing to improved patient treatment adherence and outcomes. - Biomedical Engineering, Materials Engineering, Mechanical and Industrial Engineering
- Internship, Master Thesis, Semester Project
| Online learning-aided visual inertial odometry for robust state estimation - Engineering and Technology
- Master Thesis
| Soft robots, characterized by highly flexible components, hold the potential to attain remarkable locomotion capabilities that surpass those of traditional rigid robots. However, effectively modeling, simulating, and controlling these advanced designs present significant challenges. The nonlinear dynamics inherent in these systems elude accurate representation by model-based controllers, while model-free algorithms face limitations in accessing efficient simulation environments necessary for agent training. Thus, developing robust and effective reinforcement learning (RL) approaches tailored to the unique characteristics of soft robots is imperative. In this student project, we aim to explore and apply RL techniques to enhance the locomotion performance of soft robots by addressing the aforementioned challenges. Through innovative modeling strategies, sophisticated simulation environments, and state-of-the-art model-free RL algorithms, we seek to unlock the full potential of legged robots with flexible components, enabling them to achieve exceptional locomotion capabilities and pave the way for advancements in this field. - Engineering and Technology
- Master Thesis
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