We are happy to announce that our work “QDP: Learning to Sequentially Optimise Quasi-Static and Dynamic Manipulation Primitives for Robotic Cloth Manipulation” was accepted to IROS 2023.
We participated at the Cloth Manipulation and Perception Track at the IEEE ICRA 2023 Robotic Grasping and Manipulation Competition.
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.
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.