25 citations · 56 across the 18 of their papers we have counts for
19 papers
Adaptive AI: Energy Efficient Multi-exit TinyML on Intelligent Vision Systems at the Edge
Luca Crupi, Lorenzo Lamberti, Alessandro Giusti +1
Traditional TinyML systems for edge devices achieve high accuracy by relying on fixed-depth models that require a constant number of multiply-accumulate (MAC) operations regardless…
Thinking Fast, Thinking Slow: Adaptive Multimodal Transformer-based Sensor Fusion for Depth Estimation on Ultra-low-power MCUs
Luca Crupi, Lorenzo Lamberti, Giovanni Badaracco +3
Artificial intelligence (AI)-based multimodal sensor fusion is a relevant topic gaining ever more traction across ultra-low-power (ULP) embedded and cyber-physical systems, as it i…
Towards Real-World Applications with an Autonomous Powered Wheelchair
Simone Arreghini, Alessandro Giusti, Alex Bordini +3
Wheelchair users call for assistive mobility systems that provide active support, adapt to dynamic environments, and are intuitive and user-friendly. However, powered wheelchairs t…
Exploring Human-Robot Collaboration: Analysis of Interaction Modalities in Challenging Tasks
Simone Arreghini, Cristina Iani, Alessandro Giusti +3
This work compares three interaction modalities for human-robot collaboration: passive, reactive, and proactive. We studied 18 participants assembling a seven-layer colored tower f…
User-Tailored Learning to Forecast Walking Modes for Exosuits
Gabriele Abbate, Enrica Tricomi, Nathalie Gierden +3
Assistive robotic devices, like soft lower-limb exoskeletons or exosuits, are widely spreading with the promise of helping people in everyday life. To make such systems adaptive to…
NanoCockpit: Performance-optimized Application Framework for AI-based Autonomous Nanorobotics
Elia Cereda, Alessandro Giusti, Daniele Palossi
Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad applicability and pushing scien…
An Efficient Ground-aerial Transportation System for Pest Control Enabled by AI-based Autonomous Nano-UAVs
Luca Crupi, Luca Butera, Alberto Ferrante +2
Efficient crop production requires early detection of pest outbreaks and timely treatments; we consider a solution based on a fleet of multiple autonomous miniaturized unmanned aer…
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…
A Sim-to-Real Deep Learning-based Framework for Autonomous Nano-drone Racing
Lorenzo Lamberti, Elia Cereda, Gabriele Abbate +7
Autonomous drone racing competitions are a proxy to improve unmanned aerial vehicles' perception, planning, and control skills. The recent emergence of autonomous nano-sized drone…
Self-Supervised Prediction of the Intention to Interact with a Service Robot
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck +2
A service robot can provide a smoother interaction experience if it has the ability to proactively detect whether a nearby user intends to interact, in order to adapt its behavior…
Deep Neural Network Architecture Search for Accurate Visual Pose Estimation aboard Nano-UAVs
Elia Cereda, Luca Crupi, Matteo Risso +5
Miniaturized autonomous unmanned aerial vehicles (UAVs) are an emerging and trending topic. With their form factor as big as the palm of one hand, they can reach spots otherwise in…