39 citations · 84 across the 20 of their papers we have counts for
21 papers
Factorized Spatio-Temporal Convolutions for Human Pose Estimation from Planar Lidar
Simone Arreghini, Mirko Nava, Nicholas Carlotti +2
Localizing nearby humans and estimating their facing direction are key capabilities for safe navigation and socially aware human-robot interaction. Many pose-estimation pipelines t…
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…
Sixth-Sense: Self-Supervised Learning of Spatial Awareness of Humans from a Planar Lidar
Simone Arreghini, Nicholas Carlotti, Mirko Nava +2
Reliable localization of people is fundamental for service and social robots that must operate in close interaction with humans. State-of-the-art human detectors often rely on RGB-…
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…
Exact schedulability test for sporadic mixed-criticality real-time systems using antichains and oracles
Simon Picard, Antonio Paolillo, Gilles Geeraerts +1
This work addresses the problem of exact schedulability assessment in uniprocessor mixed-criticality real-time systems with sporadic task sets. We model the problem by means of a f…
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…
Imitation Learning-based Direct Visual Servoing using the Large Projection Formulation
Sayantan Auddy, Antonio Paolillo, Justus Piater +1
Today robots must be safe, versatile, and user-friendly to operate in unstructured and human-populated environments. Dynamical system-based imitation learning enables robots to per…
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…
Imitation Learning-based Visual Servoing for Tracking Moving Objects
Rocco Felici, Matteo Saveriano, Loris Roveda +1
In everyday life collaboration tasks between human operators and robots, the former necessitate simple ways for programming new skills, the latter have to show adaptive capabilitie…
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…
Visual Servoing with Geometrically Interpretable Neural Perception
Antonio Paolillo, Mirko Nava, Dario Piga +1
An increasing number of nonspecialist robotic users demand easy-to-use machines. In the context of visual servoing, the removal of explicit image processing is becoming a trend, al…
Learning Stable Dynamical Systems for Visual Servoing
Antonio Paolillo, Matteo Saveriano
This work presents the dual benefit of integrating imitation learning techniques, based on the dynamical systems formalism, with the visual servoing paradigm. On the one hand, dyna…
Verifying and Optimizing Compact NUMA-Aware Locks on Weak Memory Models
Antonio Paolillo, Hernán Ponce-de-León, Thomas Haas +4
Developing concurrent software is challenging, especially if it has to run on modern architectures with Weak Memory Models (WMMs) such as ARMv8, Power, or RISC-V. For the sake of p…
Uncertainty-Aware Self-Supervised Learning of Spatial Perception Tasks
Mirko Nava, Antonio Paolillo, Jérôme Guzzi +2
We propose a general self-supervised learning approach for spatial perception tasks, such as estimating the pose of an object relative to the robot, from onboard sensor readings. T…
A memory of motion for visual predictive control tasks
Antonio Paolillo, Teguh Santoso Lembono, Sylvain Calinon
This paper addresses the problem of efficiently achieving visual predictive control tasks. To this end, a memory of motion, containing a set of trajectories built off-line, is used…
Memory of Motion for Warm-starting Trajectory Optimization
Teguh Santoso Lembono, Antonio Paolillo, Emmanuel Pignat +1
Trajectory optimization for motion planning requires good initial guesses to obtain good performance. In our proposed approach, we build a memory of motion based on a database of r…
Energy Minimization for Parallel Real-Time Systems with Malleable Jobs and Homogeneous Frequencies
Nathan Fisher, Joël Goossens, Pradeep M. Hettiarachchi +1
In this work, we investigate the potential utility of parallelization for meeting real-time constraints and minimizing energy. We consider malleable Gang scheduling of implicit-dea…