3 papers
cs.RO2024
Dynamic Manipulation of Deformable Objects using Imitation Learning with Adaptation to Hardware Constraints
Eric Hannus, Tran Nguyen Le, David Blanco-Mulero +1
Imitation Learning (IL) is a promising paradigm for learning dynamic manipulation of deformable objects since it does not depend on difficult-to-create accurate simulations of such…
cs.RO2023
Benchmarking the Sim-to-Real Gap in Cloth Manipulation
David Blanco-Mulero, Oriol Barbany, Gokhan Alcan +3
Realistic physics engines play a crucial role for learning to manipulate deformable objects such as garments in simulation. By doing so, researchers can circumvent challenges such…
cs.LG2021
Evolving-Graph Gaussian Processes
David Blanco-Mulero, Markus Heinonen, Ville Kyrki
Graph Gaussian Processes (GGPs) provide a data-efficient solution on graph structured domains. Existing approaches have focused on static structures, whereas many real graph data r…