Fabio Amadio — accepted AI-conference papers

2022

A Target-Guided Telemanipulation Architecture for Assisted Grasping

Marco Laghi, Luigi Raiano, Fabio Amadio, Federico Rollo, Andrea Zunino, Arash Ajoudani

RA-L 2022

Teleoperation offers the possibility to combine human intelligence with robot power and endurance, making it a perfect solution for hostile-for-human environments. Nonetheless, when it concerns prolonged and repetitive operations, classical teleoperation interfaces that replicate one-to-one human co

Cited by 15 Source ↗Scholar ↗

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 ↗