David Blanco Mulero

2 accepted papers

2024

Benchmarking the Sim-to-Real Gap in Cloth Manipulation

David Blanco Mulero, Oriol Barbany, Gokhan Alcan, Adrià Colomé, Carme Torras, Ville Kyrki

RA-L 2024

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 as sensing the deformation of the object in the realworld. In spite of the extensive use of simulations for this task, f

Cited by 28 Source ↗Scholar ↗

2022

Manipulation of Granular Materials by Learning Particle Interactions

Neea Tuomainen, David Blanco Mulero, Ville Kyrki

RA-L 2022

Manipulation of granular materials such as sand or rice remains an unsolved problem due to challenges such as the difficulty of defining their configuration or modeling the materials and their particles interactions. Current approaches tend to simplify the material dynamics and omit the interactions

Cited by 25 Source ↗code ↗Scholar ↗