Robotics and Perception

Open Opportunities

Advancing Space Navigation and Landing with Event-Based Camera in collaboration with the European Space Agency University of Zurich Robotics and Perception In this project, you will investigate the use of event-based cameras for vision-based landing on celestial bodies such as Mars or the Moon. Engineering and Technology Master Thesis

Time-continuous Facial Motion Capture Using Event Cameras University of Zurich Robotics and Perception Traditional facial motion capture systems, including marker-based methods and multi-camera rigs, often struggle to capture fine details such as micro-expressions and subtle wrinkles. While learning-based techniques using monocular RGB images have improved tracking fidelity, their temporal resolution remains limited by conventional camera frame rates. Event-based cameras present a compelling solution, offering superior temporal resolution without the cost and complexity of high-speed RGB cameras. This project explores the potential of event-based cameras to enhance facial motion tracking, enabling the precise capture of subtle facial dynamics over time. Engineering and Technology Bachelor Thesis, Master Thesis, Semester Project

Better Scaling Laws for Neuromorphic Systems University of Zurich Robotics and Perception This project explores and extends the novel "deep state-space models" framework by leveraging their transfer function representations. Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences Master Thesis, Semester Project

Electrical Flow-Based Graph Embeddings for Event-based Vision and other downstream tasks University of Zurich Robotics and Perception This project explores a novel approach to graph embeddings using electrical flow computations. Artificial Intelligence and Signal and Image Processing, Knowledge Representation and Machine Learning, Mathematics Master Thesis

Leveraging Long Sequence Modeling for Drone Racing University of Zurich Robotics and Perception Study the application of Long Sequence Modeling techniques within Reinforcement Learning (RL) to improve autonomous drone racing capabilities. Engineering and Technology, Information, Computing and Communication Sciences Master Thesis

Neural Architecture Knowledge Transfer for Event-based Vision University of Zurich Robotics and Perception 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

Learning Robust Agile Flight via Adaptive Curriculum University of Zurich Robotics and Perception This project focuses on developing robust reinforcement learning controllers for agile drone navigation using adaptive curricula. Commonly, these controllers are trained with a static, pre-defined curriculum. The goal is to develop a dynamic, adaptive curriculum that evolves online based on the agents' performance to increase the robustness of the controllers. Engineering and Technology Master Thesis, Semester Project

Improving SLAM in the Operating Room Using Event Cameras University of Zurich Robotics and Perception Other organizations: Research in Orthopedic Computer Science This project focuses on enhancing SLAM (Simultaneous Localization and Mapping) in operating rooms using event cameras, which outperform traditional cameras in dynamic range, motion blur, and temporal resolution. By leveraging these capabilities, the project aims to develop a robust, real-time SLAM system tailored for surgical environments, addressing challenges like high-intensity lighting and head movement-induced motion blur. Engineering and Technology, Information, Computing and Communication Sciences Master Thesis, Semester Project

Generating Realistic Event Camera Data with Generative AI University of Zurich Robotics and Perception In this project, the student applies concepts from current advances in image generation to create artificial events from standard frames. Multiple state-of-the-art deep learning methods will be explored in the scope of this project. Artificial Intelligence and Signal and Image Processing Master Thesis, Semester Project

Enhancing Robotic Motor Policies with Event Cameras University of Zurich Robotics and Perception The goal of this project is to develop a shared embedding space for events and frames, enabling the training of a motor policy on simulated frames and deployment on real-world event data. Artificial Intelligence and Signal and Image Processing Master Thesis, Semester Project