5 papers
Dynamic robotic cloth folding with efficient Koopman operator-based model predictive control
Edoardo Caldarelli, Franco Coltraro, Adrià Colomé +2
Robotic cloth folding is a challenging task, particularly when considering dynamic folding tasks, which aim at folding cloth by fast motions that leverage its dynamics. When subjec…
Beyond Static Perception: Integrating Temporal Context into VLMs for Cloth Folding
Oriol Barbany, Adrià Colomé, Carme Torras
Manipulating clothes is challenging due to their complex dynamics, high deformability, and frequent self-occlusions. Garments exhibit a nearly infinite number of configurations, ma…
BiFold: Bimanual Cloth Folding with Language Guidance
Oriol Barbany, Adrià Colomé, Carme Torras
Cloth folding is a complex task due to the inevitable self-occlusions of clothes, their complicated dynamics, and the disparate materials, geometries, and textures that garments ca…
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé +4
In this paper, we study how the Koopman operator framework can be combined with kernel methods to effectively control nonlinear dynamical systems. While kernel methods have typical…
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…