activity
20232026
collaborators

6 papers

cs.CV2026

A Baseline Study and Benchmark for Few-Shot Open-Set Action Recognition with Feature Residual Discrimination

Stefano Berti, Giulia Pasquale, Lorenzo Natale

Few-Shot Action Recognition (FS-AR) has shown promising results but is often limited by a closed-set assumption that fails in real-world open-set scenarios. While Few-Shot Open-Set…

cs.RO2025

KDPE: A Kernel Density Estimation Strategy for Diffusion Policy Trajectory Selection

Andrea Rosasco, Federico Ceola, Giulia Pasquale +1

Learning robot policies that capture multimodality in the training data has been a long-standing open challenge for behavior cloning. Recent approaches tackle the problem by modeli…

cs.RO2025

PCHands: PCA-based Hand Pose Synergy Representation on Manipulators with N-DoF

En Yen Puang, Federico Ceola, Giulia Pasquale +1

We consider the problem of learning a common representation for dexterous manipulation across manipulators of different morphologies. To this end, we propose PCHands, a novel appro…

cs.RO2025

HannesImitation: Grasping with the Hannes Prosthetic Hand via Imitation Learning

Carlo Alessi, Federico Vasile, Federico Ceola +3

Recent advancements in control of prosthetic hands have focused on increasing autonomy through the use of cameras and other sensory inputs. These systems aim to reduce the cognitiv…

cs.RO2024

RESPRECT: Speeding-up Multi-fingered Grasping with Residual Reinforcement Learning

Federico Ceola, Lorenzo Rosasco, Lorenzo Natale

Deep Reinforcement Learning (DRL) has proven effective in learning control policies using robotic grippers, but much less practical for solving the problem of grasping with dextero…

cs.RO2023

LHManip: A Dataset for Long-Horizon Language-Grounded Manipulation Tasks in Cluttered Tabletop Environments

Federico Ceola, Lorenzo Natale, Niko Sünderhauf +1

Instructing a robot to complete an everyday task within our homes has been a long-standing challenge for robotics. While recent progress in language-conditioned imitation learning…