Robotics and Perception

Open Opportunities

Probabilistic System Identification of a Quadrotor Platform University of Zurich Robotics and Perception This work investigates the usage of Gaussian Processes for uncertainty-aware system identification of a quadrotor platform. Automotive Engineering Master Thesis, Semester Project

Why so complicated? Global localization without fuss University of Zurich Robotics and Perception Achieve comparable or better place recognition performance than NetVLAD, with a simpler network architecture. Computer Vision Master Thesis

One net to rule them all (global localization and pose estimation) University of Zurich Robotics and Perception Combine state-of-the-art place embedding and feature extraction networks into a single network and train them jointly. Computer Vision Master Thesis

Data-Driven Visual Inertial Odometry for Quadrotor Flight University of Zurich Robotics and Perception Investigate the usability of data-driven methods to improve the performance of a VIO pipeline on a resource-constrained platform. Automotive Engineering Master Thesis, Semester Project

Learning to Deblur Images with Events University of Zurich Robotics and Perception Explore machine learning based approaches for deblurring of images with events Computer Vision, Image Processing, Pattern Recognition Master Thesis, Semester Project

Simulation to Real World Transfer University of Zurich Robotics and Perception The project aims to develop techniques based on machine learning to have maximal knowledge transfer between simulated and real world on a navigation task. Intelligent Robotics Bachelor Thesis, Master Thesis, Semester Project

Unsupervised Obstacle Detection Learning University of Zurich Robotics and Perception In this project, we aim to build a self-supervised depth estimation and segmentation algorithm by embedding classic computer vision principles (e.g. brightness constancy) into a neural network. Computer Vision, Intelligent Robotics, Knowledge Representation and Machine Learning Master Thesis, Semester Project

Target following on nano-scale UAV University of Zurich Robotics and Perception This project focuses on the object tracking, (i.e., target following) on nano-UAVs (few centimeters in size). Computer Vision, Intelligent Robotics Master Thesis, Semester Project

Ground Segmentation for Landing University of Zurich Robotics and Perception In order for UAVs to fly and especially land autonomously we need evaluate the safety of landing spots. Having semantic information about the scenery, eg. road, forest, roof, etc, enables the UAV to pick a safe landing spot. Engineering and Technology Master Thesis, Semester Project

Robustification of Vision-Based Drone Navigation University of Zurich Robotics and Perception VIO system are used to navigate drones in GPS denied environments. These systems are, however, prone to failure, for example due to loss of feature tracking. This will result in a crash, as the drone has no knowledge about its own state. However, if the drone manges to hold its position without the VIO system for some time, the VIO pipeline can be reinitialised and the navigation task can continue. Additionally, it will also prevent a crash, increasing the safety. The images from the camera and IMU data are usually still available when the VIO pipeline crashes. Engineering and Technology Master Thesis, Semester Project