25 citations · 56 across the 18 of their papers we have counts for
9 papers · 1 filter
Hearing the Robot's Mind: Sonification for Explicit Feedback in Human-Robot Interaction
Simone Arreghini, Antonio Paolillo, Gabriele Abbate +1
Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use…
Learning Hand State Estimation for a Light Exoskeleton
Gabriele Abbate, Alessandro Giusti, Luca Randazzo +1
We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domes…
A Service Robot in the Wild: Analysis of Users Intentions, Robot Behaviors, and Their Impact on the Interaction
Simone Arreghini, Gabriele Abbate, Alessandro Giusti +1
We consider a service robot that offers chocolate treats to people passing in its proximity: it has the capability of predicting in advance a person's intention to interact, and to…
Systematic analysis of requirements for socially acceptable service robots
Andrea Ruo, Simone Arreghini, Luca Capra +13
In modern society, service robots are increasingly recognized for their wide range of practical applications. In large and crowded social spaces, such as museums and hospitals, the…
Training on the Fly: On-device Self-supervised Learning aboard Nano-drones within 20 mW
Elia Cereda, Alessandro Giusti, Daniele Palossi
Miniaturized cyber-physical systems (CPSes) powered by tiny machine learning (TinyML), such as nano-drones, are becoming an increasingly attractive technology. Their small form fac…
Predicting the Intention to Interact with a Service Robot:the Role of Gaze Cues
Simone Arreghini, Gabriele Abbate, Alessandro Giusti +1
For a service robot, it is crucial to perceive as early as possible that an approaching person intends to interact: in this case, it can proactively enact friendly behaviors that l…
On-device Self-supervised Learning of Visual Perception Tasks aboard Hardware-limited Nano-quadrotors
Elia Cereda, Manuele Rusci, Alessandro Giusti +1
Sub-\SI{50}{\gram} nano-drones are gaining momentum in both academia and industry. Their most compelling applications rely on onboard deep learning models for perception despite se…
Self-Supervised Learning of Visual Robot Localization Using LED State Prediction as a Pretext Task
Mirko Nava, Nicholas Carlotti, Luca Crupi +2
We propose a novel self-supervised approach for learning to visually localize robots equipped with controllable LEDs. We rely on a few training samples labeled with position ground…
High-throughput Visual Nano-drone to Nano-drone Relative Localization using Onboard Fully Convolutional Networks
Luca Crupi, Alessandro Giusti, Daniele Palossi
Relative drone-to-drone localization is a fundamental building block for any swarm operations. We address this task in the context of miniaturized nano-drones, i.e., 10cm in diamet…