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ICRA 2023, here we come!
The Intelligent Robotics group will attend to ICRA 2023. Read more!
Master thesis on “Development of data-driven driver model”
This thesis aims to develop data-driven driver models using expert data. Many real-world driving datasets with diverse driving scenarios and closed-loop evaluation frameworks are currently available from Waymo, NuPlan, and Lyft.
Our work “Learning Visual Feedback Control for Dynamic Cloth Folding” was accepted to IROS 2022!
We are happy to announce that our work “Learning Visual Feedback Control for Dynamic Cloth Folding” was accepted to IROS 2022 and nomitated to both the IROS Best Paper award, Best Student Paper award and the IROS Best RoboCup Paper Award.
Manipulation of Granular Materials by Learning Particle Interactions
In this work we propose to use a Graph Neural Network (GNN) surrogate model to learn the particle interactions of granular materials. We perform planning of manipulation trajectories with the learnt surrogate model to arrange the material into a desired configuration.
Season-invariant GNSS-denied visual localization for UAVs
This repository contains data and code for manuscript J. Kinnari, F. Verdoja, V. Kyrki “Season-invariant GNSS-denied visual localization for UAVs”.
Soft Robotic Hand
Robotic grasping has been studied for more than 30 years, but it is still a challenging field. Today, most robotic grippers are rigid, making it hard for them to grasp and handle irregularly shaped objects that are delicate and easily deformed such as a compact disc, an egg, or an empty plastic cup. To tackle […]
Exploiting Object Physical Properties for Grasping
In robotic manipulation, robots are required to interact with, and adapt to, unknown environments and objects. In order to successfully accomplish these tasks, robots need to identify various properties of the objects to be handled. For these reasons, identifying object models that can represent the properties of objects has become a crucial issue in robotics. […]