22 citations · 77 across the 15 of their papers we have counts for
15 papers
Bring Your Own Grasp Generator: Leveraging Robot Grasp Generation for Prosthetic Grasping
Giuseppe Stracquadanio, Federico Vasile, Elisa Maiettini +2
One of the most important research challenges in upper-limb prosthetics is enhancing the user-prosthesis communication to closely resemble the experience of a natural limb. As pros…
Continuous Wrist Control on the Hannes Prosthesis: a Vision-based Shared Autonomy Framework
Federico Vasile, Elisa Maiettini, Giulia Pasquale +2
Most control techniques for prosthetic grasping focus on dexterous fingers control, but overlook the wrist motion. This forces the user to perform compensatory movements with the e…
Gaze estimation learning architecture as support to affective, social and cognitive studies in natural human-robot interaction
Maria Lombardi, Elisa Maiettini, Agnieszka Wykowska +1
Gaze is a crucial social cue in any interacting scenario and drives many mechanisms of social cognition (joint and shared attention, predicting human intention, coordination tasks)…
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis
Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3
This study provides a comprehensive benchmark framework for Source-Free Unsupervised Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical unde…
iCub Detecting Gazed Objects: A Pipeline Estimating Human Attention
Shiva Hanifi, Elisa Maiettini, Maria Lombardi +1
This research report explores the role of eye gaze in human-robot interactions and proposes a learning system for detecting objects gazed at by humans using solely visual feedback.…
A Grasp Pose is All You Need: Learning Multi-fingered Grasping with Deep Reinforcement Learning from Vision and Touch
Federico Ceola, Elisa Maiettini, Lorenzo Rosasco +1
Multi-fingered robotic hands have potential to enable robots to perform sophisticated manipulation tasks. However, teaching a robot to grasp objects with an anthropomorphic hand is…
Key Design Choices for Double-Transfer in Source-Free Unsupervised Domain Adaptation
Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3
Fine-tuning and Domain Adaptation emerged as effective strategies for efficiently transferring deep learning models to new target tasks. However, target domain labels are not acces…
iCub Knows Where You Look: Exploiting Social Cues for Interactive Object Detection Learning
Maria Lombardi, Elisa Maiettini, Vadim Tikhanoff +1
Performing joint interaction requires constant mutual monitoring of own actions and their effects on the other's behaviour. Such an action-effect monitoring is boosted by social cu…
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot
Federico Ceola, Elisa Maiettini, Giulia Pasquale +3
The visual system of a robot has different requirements depending on the application: it may require high accuracy or reliability, be constrained by limited resources or need fast…
Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis
Federico Vasile, Elisa Maiettini, Giulia Pasquale +3
We consider the task of object grasping with a prosthetic hand capable of multiple grasp types. In this setting, communicating the intended grasp type often requires a high user co…
Weakly-Supervised Object Detection Learning through Human-Robot Interaction
Elisa Maiettini, Vadim Tikhanoff, Lorenzo Natale
Reliable perception and efficient adaptation to novel conditions are priority skills for humanoids that function in dynamic environments. The vast advancements in latest computer v…
From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning Approach
Elisa Maiettini, Andrea Maracani, Raffaello Camoriano +4
Deep Learning (DL) based methods for object detection achieve remarkable performance at the cost of computationally expensive training and extensive data labeling. Robots embodimen…
Fast Object Segmentation Learning with Kernel-based Methods for Robotics
Federico Ceola, Elisa Maiettini, Giulia Pasquale +2
Object segmentation is a key component in the visual system of a robot that performs tasks like grasping and object manipulation, especially in presence of occlusions. Like many ot…
Fast Region Proposal Learning for Object Detection for Robotics
Federico Ceola, Elisa Maiettini, Giulia Pasquale +2
Object detection is a fundamental task for robots to operate in unstructured environments. Today, there are several deep learning algorithms that solve this task with remarkable pe…
Speeding-up Object Detection Training for Robotics with FALKON
Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco +1
Latest deep learning methods for object detection provide remarkable performance, but have limits when used in robotic applications. One of the most relevant issues is the long tra…