Adria Colome — accepted AI-conference papers

2019

Exploiting Symmetries in Reinforcement Learning of Bimanual Robotic Tasks

Fabio Amadio, Adria Colome, Carme Torras

RA-L 2019

Movement primitives (MPs) have been widely adopted for representing and learning robotic movements using reinforcement learning policy search. Probabilistic movement primitives (ProMPs) are a kind of MP based on a stochastic representation over sets of trajectories, able to capture the variability a

Cited by 33 Source ↗Scholar ↗

2018

Dimensionality Reduction in Learning Gaussian Mixture Models of Movement Primitives for Contextualized Action Selection and Adaptation

Adria Colome, Carme Torras

RA-L 2018

Robotic manipulation often requires adaptation to changing environments. Such changes can be represented by a certain number of contextual variables that may be observed or sensed in different manners. When learning and representing robot motion-usually with movement primitives, it is desirable to a

Cited by 12 Source ↗Scholar ↗