5 citations · 10 across the 22 of their papers we have counts for
26 papers
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…
Trajectory-Safe Orienteering for Human-Robot Shared Environments
Songqun Gao, Elena Basei, Marco Roveri +2
Orienteering problem (OP) has wide real-world applications and also great potential in human-robot collaboration. However, existing approaches struggle to simultaneously ensure saf…
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…
UNSEEN: Uncertainty-aware Navigation via Sparse Estimation in Unknown Environments
Tommaso Faraci, Marco Camurri, Daniele Fontanelli +1
Visual navigation in unknown environments remains a core challenge in mobile robotics, especially for resource-constrained platforms. Most existing approaches rely on loosely coupl…
Learning to Solve Orienteering Problem with Time Windows and Variable Profits
Songqun Gao, Zanxi Ruan, Patrick Floor +3
The orienteering problem with time windows and variable profits (OPTWVP) is common in many real-world applications and involves continuous time variables. Current approaches fail t…
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…
Force-Based Viscosity and Elasticity Measurements for Material Biomechanical Characterisation with a Collaborative Robotic Arm
Luca Beber, Edoardo Lamon, Giacomo Moretti +4
Diagnostic activities, such as ultrasound scans and palpation, are relatively low-cost. They play a crucial role in the early detection of health problems and in assessing their pr…
Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robots
Riccardo Bussola, Michele Focchi, Giulio Turrisi +2
Jumping poses a significant challenge for quadruped robots, despite being crucial for many operational scenarios. While optimisation methods exist for controlling such motions, the…
Extracting Visual Plans from Unlabeled Videos via Symbolic Guidance
Wenyan Yang, Ahmet Tikna, Yi Zhao +4
Visual planning, by offering a sequence of intermediate visual subgoals to a goal-conditioned low-level policy, achieves promising performance on long-horizon manipulation tasks. T…
Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases
Enrico Saccon, Matteo Saveriano, Edoardo Lamon +2
We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted knowledge-base construction. The ap…
Learning Priors of Human Motion With Vision Transformers
Placido Falqueto, Alberto Sanfeliu, Luigi Palopoli +1
A clear understanding of where humans move in a scenario, their usual paths and speeds, and where they stop, is very important for different applications, such as mobility studies…
Surface Defect Identification using Bayesian Filtering on a 3D Mesh
Matteo Dalle Vedove, Matteo Bonetto, Edoardo Lamon +3
This paper presents a CAD-based approach for automated surface defect detection. We leverage the a-priori knowledge embedded in a CAD model and integrate it with point cloud data a…
Socially-Aware Opinion-Based Navigation with Oval Limit Cycles
Giulia d'Addato, Placido Falqueto, Luigi Palopoli +1
When humans move in a shared space, they choose navigation strategies that preserve their mutual safety. At the same time, each human seeks to minimise the number of modifications…
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…
Pseudo-Kinematic Trajectory Control and Planning of Tracked Vehicles
Michele Focchi, Daniele Fontanelli, Davide Stocco +2
Tracked vehicles distribute their weight continuously over a large surface area (the tracks). This distinctive feature makes them the preferred choice for vehicles required to trav…
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…
Fast Shortest Path Polyline Smoothing With Continuity and Bounded Curvature
Patrick Pastorelli, Simone Dagnino, Enrico Saccon +2
In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature.…
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…
Joint torques prediction of a robotic arm using neural networks
Giulia d'Addato, Ruggero Carli, Eurico Pedrosa +3
Accurate dynamic models are crucial for many robotic applications. Traditional approaches to deriving these models are based on the application of Lagrangian or Newtonian mechanics…
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…
ALPINE: a climbing robot for operations in mountain environments
Michele Focchi, Andrea Del Prete, Daniele Fontanelli +3
Mountain slopes are perfect examples of harsh environments in which humans are required to perform difficult and dangerous operations such as removing unstable boulders, dangerous…