5 papers
MultiGraspNet: A Multitask 3D Vision Model for Multi-gripper Robotic Grasping
Stephany Ortuno-Chanelo, Paolo Rabino, Enrico Civitelli +2
Vision-based models for robotic grasping automate critical, repetitive, and draining industrial tasks. Existing approaches are typically limited in two ways: they either target a s…
MaskPlanner: Learning-Based Object-Centric Motion Generation from 3D Point Clouds
Gabriele Tiboni, Raffaello Camoriano, Tatiana Tommasi
Object-Centric Motion Generation (OCMG) plays a key role in a variety of industrial applications$\unicode{x2014}$such as robotic spray painting and welding$\unicode{x2014}$requirin…
Continual Learning Should Move Beyond Incremental Classification
Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano +17
Continual learning (CL) is the sub-field of machine learning concerned with accumulating knowledge in dynamic environments. So far, CL research has mainly focused on incremental cl…
Long-Term Upper-Limb Prosthesis Myocontrol via High-Density sEMG and Incremental Learning
Dario Di Domenico, Nicolò Boccardo, Andrea Marinelli +4
Noninvasive human-machine interfaces such as surface electromyography (sEMG) have long been employed for controlling robotic prostheses. However, classical controllers are limited…
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers
Eros Fanì, Raffaello Camoriano, Barbara Caputo +1
Federated Learning (FL) methods often struggle in highly statistically heterogeneous settings. Indeed, non-IID data distributions cause client drift and biased local solutions, par…