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Autonomous mapping systems can provide crucial information for agricultural monitoring and industrial inspection tasks. They aim to map unknown environments without human intervention using online mission planning. Many approaches for online mission planning exist but only a few can handle the presence of dynamic obstacles [1-3], which produce moving occlusions and can result in incomplete maps. - Computer Vision, Intelligent Robotics, Robotics and Mechatronics
- Master Thesis, Semester Project
| Automating drone navigation promises to revolutionise the way we conduct a wide variety of tasks, such as agricultural monitoring, industrial inspection, and disaster relief scenarios. Equipping a drone with the capability to autonomously explore and map previously unseen environments using onboard sensors and algorithms forms the basis of autonomy. While there has been tremendous progress in this area over the past few years [1-5], existing systems still lack reliability and adaptability to the challenges and complexity of real settings, which is crucial for the deployment of this technology in actual missions. In particular, performing robust navigation and mapping in highly dynamic environments (e.g., forests) remains an open challenge.
Following promising leads from the state-of-the-art and our in-house navigation stack, the goal of this project is to develop the capability to deal with increasingly dynamic and complex scenarios. The student will be guided towards leveraging the multi-sensor capabilities of a LiDAR-Visual-Inertial payload being developed in the lab to research approaches for perception and mission planning that can fuse information from the different sensors and capture high-fidelity representations of challenging dynamic environments. Initially, the student will work within a realistic simulation environment and then deploy and test their work onboard a real drone in a real setting.
- Computer Vision, Intelligent Robotics
- Master Thesis
| We are looking for bachelor / master students to work part time to support the development of robotic platforms and assist with the preparations and execution of the Robotics Summer School taking place from 22 June through 27 June 2025. - Engineering and Technology
- Student Assistant / HiWi
| Navigation of ANYmal using Diffusion Policy including real-world experiments and deployment.
References
[1] Reuss, Moritz, et al. "Goal-conditioned imitation learning using score-based diffusion policies." RSS 2023
[2] Shah, Dhruv, et al. "ViNT: A foundation model for visual navigation." CoRL 2023
[3] Sridhar, Ajay, et al. "Nomad: Goal masked diffusion policies for navigation and exploration." 2024 (ICRA). IEEE, 2024.
- Computer Communications Networks, Computer Graphics, Computer Hardware, Computer Perception, Memory and Attention, Computer Vision, Computer-Human Interaction, Engineering/Technology Instrumentation, Intelligent Robotics, Robotics and Mechatronics, Software Engineering
- Master Thesis, Semester Project
| Perform knowledge distillation from Transformers to more energy-efficient neural network architectures for Event-based Vision. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| 1 July - 3 September. ETH Zurich offers scholarships for a summer research stay within the Amgen Scholars Program. The programme applies to students studying for a Bachelor’s degree at a European university. - Biochemistry and Cell Biology, Biomedical Engineering, Biotechnology, Chemical Engineering, Computational Biology and Bioinformatics, Medical Biochemistry and Clinical Chemistry, Neurosciences, Pharmacology and Pharmaceutical Sciences
- ETH Amgen Scholars Program (ETHZ), Internship, Lab Practice
| Explore novel ideas for low-cost but stable training of Neural Networks. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Robotic automation represents mankind’s next leap. While the industry has already embraced robotization, robot driven domestic aid is only at the beginning of the revolution. Dealing with unconstrained daily environments is more challenging than automating manufacturing production lines. The growing diffusion of semi-autonomous assistive quadrupedal robots that can handle obstacles triggered the change. Nonetheless, robot control still requires active human supervision, which can be tedious in ordinary surroundings or even impossible in clinical circumstances. - Electrical Engineering
- Computer Vision (PBL), Master Thesis, Robotics (PBL), Software (PBL)
| The resolution of clinical CT images is not sufficient to characterize the complex network of trabecular bone. The student will develop a Super Resolution pipeline to enhance CT images and enable a characterization of the microarchitecture of human bone. - Biomechanical Engineering, Image Processing, Materials Engineering, Mechanical Engineering, Medical Physics
- ETH Zurich (ETHZ), Master Thesis
| Develop a Fourier transform profilometry system to measure the elevation of the wavy water surface generated by wind blowing over the water. - Fluid Physics, Mechanical Engineering, Oceanography
- Master Thesis
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