2 citations · 4 across the 11 of their papers we have counts for
12 papers · 1 filter
Robot Learning on Discrete Surfaces: Theory and Applications
Matteo Dalle Vedove, Fares J. Abu-Dakka, Luigi Palopoli +2
All the objects composing our world are enclosed within surfaces. Yet, most robot learning and motion generation frameworks treat surfaces as constraints ignoring their intrinsic g…
Proactive Motion Planning for Human-Robot Cooperation
Elena Basei, Edoardo Lamon, Matteo Saveriano +2
This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling safe collaboration between hu…
Human Motion Prediction for Human-Robot Collaboration
Placido Falqueto, Elena Basei, Edoardo Lamon +4
This paper compares three human motion prediction methods - GMM-based clustering, TransFusion, and Graph-Mixer - evaluating their effectiveness in human-robot collaboration. These…
VLMs Can Describe, But Not Measure: Object-Centric Scene Understanding for Robotic Manipulation
Enrico Saccon, Tommaso Faraci, Iñigo De La Ossa Zarzuelo +3
Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language models (VLMs) provide strong semant…
Autonomous Robotic Tissue Palpation and Abnormalities Characterisation via Ergodic Exploration
Luca Beber, Edoardo Lamon, Matteo Saveriano +2
We propose a novel autonomous robotic palpation framework for real-time elastic mapping during tissue exploration using a viscoelastic tissue model. The method combines force-based…
Automated Generation of MDPs Using Logic Programming and LLMs for Robotic Applications
Enrico Saccon, Davide De Martini, Matteo Saveriano +3
We present a novel framework that integrates Large Language Models (LLMs) with automated planning and formal verification to streamline the creation and use of Markov Decision Proc…
MeshDMP: Motion Planning on Discrete Manifolds using Dynamic Movement Primitives
Matteo Dalle Vedove, Fares J. Abu-Dakka, Luigi Palopoli +2
An open problem in industrial automation is to reliably perform tasks requiring in-contact movements with complex workpieces, as current solutions lack the ability to seamlessly ad…
An Anatomy-Aware Shared Control Approach for Assisted Teleoperation of Lung Ultrasound Examinations
Davide Nardi, Edoardo Lamon, Daniele Fontanelli +2
Although fully autonomous systems still face challenges due to patients' anatomical variability, teleoperated systems appear to be more practical in current healthcare settings. Th…
A Passivity-Based Variable Impedance Controller for Incremental Learning of Periodic Interactive Tasks
Matteo Dalle Vedove, Edoardo Lamon, Daniele Fontanelli +2
In intelligent manufacturing, robots are asked to dynamically adapt their behaviours without reducing productivity. Human teaching, where an operator physically interacts with the…
Towards Robotised Palpation for Cancer Detection through Online Tissue Viscoelastic Characterisation with a Collaborative Robotic Arm
Luca Beber, Edoardo Lamon, Giacomo Moretti +3
This paper introduces a new method for estimating the penetration of the end effector and the parameters of a soft body using a collaborative robotic arm. This is possible using th…
Elasticity Measurements of Expanded Foams using a Collaborative Robotic Arm
Luca Beber, Edoardo Lamon, Luigi Palopoli +3
Medical applications of robots are increasingly popular to objectivise and speed up the execution of several types of diagnostic and therapeutic interventions. Particularly importa…
A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography
Luca Beber, Edoardo Lamon, Davide Nardi +3
In the context of telehealth, robotic approaches have proven a valuable solution to in-person visits in remote areas, with decreased costs for patients and infection risks. In part…