Robotics and Perception

Open Opportunities

Agile Flight of Flexible Drones in Confined Spaces University of Zurich Robotics and Perception The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints. Control Engineering, Flight Control Systems, Intelligent Robotics, Systems Theory and Control Master Thesis, Semester Project

Vision-Based World Models for Real-Time Robot Control University of Zurich Robotics and Perception This project aims to use vision-based world models as a basis for model-based reinforcement learning, aiming to achieve a generalizable approach for drone navigation. Computer Vision, Intelligent Robotics, Simulation and Modelling Master Thesis, Semester Project

Vision-Based Reinforcement Learning in the Real World University of Zurich Robotics and Perception We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning. Computer Vision, Flight Control Systems, Intelligent Robotics Master Thesis, Semester Project

Meta-model-based-RL for adaptive flight control University of Zurich Robotics and Perception This research project aims to develop and evaluate a meta model-based reinforcement learning (RL) framework for addressing variable dynamics in flight control. Artificial Intelligence and Signal and Image Processing, Engineering and Technology Master Thesis

Language-guided Drone Control University of Zurich Robotics and Perception Explore the use of large vision language models to control a drone. Engineering and Technology, Intelligent Robotics Master Thesis, Semester Project

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