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20172026
most citedAn Ergonomic Role Allocation Framework for Dynamic Human-Robot Collaborative Tasks

75 citations · 445 across the 63 of their papers we have counts for

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53 papers · 1 filter

cs.RO2026

Graph-Based Heuristics for Minimum Constraint Removal in Cluttered Robot Motion Planning

Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto

Humanoid and service robots operating in clut- tered human environments may encounter motion planning problems that are infeasible when all surrounding objects are treated as fixed…

cs.RO2026

On Representational Alignment among Embodied Agents

Fulvio Mastrogiovanni

Embodied agents interacting with the same physical process may maintain heterogeneous, asynchronous, and observer-relative representations. Rather than assuming that such represent…

cs.RO2026

A Horizon-slicing Approach to Minimum Obstacle Displacement Planning for Robot Navigation

Antony Thomas, Giulio Ferro, Fulvio Mastrogiovanni +2

In this paper, we investigate the Minimum Obstacle Displacement Planning problem from a robot motion planning perspective. The problem involves determining a feasible path to a goa…

cs.RO2025

Locally Optimal Solutions to Constraint Displacement Problems via Path-Obstacle Overlaps

Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto

We present a unified approach for constraint displacement problems in which a robot finds a feasible path by displacing constraints or obstacles. To this end, we propose a two stag…

cs.RO2025

A Framework for Task and Motion Planning based on Expanding AND/OR Graphs

Fulvio Mastrogiovanni, Antony Thomas

Robot autonomy in space environments presents unique challenges, including high perception and motion uncertainty, strict kinematic constraints, and limited opportunities for human…

cs.RO2025

A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks

Hossein Karami, Antony Thomas, Fulvio Mastrogiovanni

In this paper, we present an approach for integrated task and motion planning based on an AND/OR graph network, which is used to represent task-level states and actions, and we lev…

cs.RO2025

An Incremental Sampling and Segmentation-Based Approach for Motion Planning Infeasibility

Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto

We present a simple and easy-to-implement algorithm to detect plan infeasibility in kinematic motion planning. Our method involves approximating the robot's configuration space to…

cs.RO2024★ 5 cited

The Effects of Selected Object Features on a Pick-and-Place Task: a Human Multimodal Dataset

Linda Lastrico, Valerio Belcamino, Alessandro Carfì +4

We propose a dataset to study the influence of object-specific characteristics on human pick-and-place movements and compare the quality of the motion kinematics extracted by vario…

cs.RO2024

Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget Experiences

Luca Buoncompagni, Fulvio Mastrogiovanni

We present a symbolic learning framework inspired by cognitive-like memory functionalities (i.e., storing, retrieving, consolidating and forgetting) to generate task representation…

cs.RO2023★ 1 cited

Digital Twins for Human-Robot Collaboration: A Future Perspective

Mohamad Shaaban, Alessandro Carfì, Fulvio Mastrogiovanni

As collaborative robot (Cobot) adoption in many sectors grows, so does the interest in integrating digital twins in human-robot collaboration (HRC). Virtual representations of phys…

cs.RO2023★ 9 cited

Expressing and Inferring Action Carefulness in Human-to-Robot Handovers

Linda Lastrico, Nuno Ferreira Duarte, Alessandro Carfì +4

Implicit communication plays such a crucial role during social exchanges that it must be considered for a good experience in human-robot interaction. This work addresses implicit c…

cs.RO2023★ 1 cited

RICO-MR: An Open-Source Architecture for Robot Intent Communication through Mixed Reality

Simone Macciò, Mohamad Shaaban, Alessandro Carfì +2

This article presents an open-source architecture for conveying robots' intentions to human teammates using Mixed Reality and Head-Mounted Displays. The architecture has been devel…

cs.RO2023★ 2 cited

In-hand manipulation planning using human motion dictionary

Ali Hammoud, Valerio Belcamino, Alessandro Carfi +2

Dexterous in-hand manipulation is a peculiar and useful human skill. This ability requires the coordination of many senses and hand motion to adhere to many constraints. These cons…

cs.RO2023★ 10 cited

Safe motion planning with environment uncertainty

Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto

We present an approach for safe motion planning under robot state and environment (obstacle and landmark location) uncertainties. To this end, we first develop an approach that acc…

cs.RO2023

Revisiting the Minimum Constraint Removal Problem in Mobile Robotics

Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto

The minimum constraint removal problem seeks to find the minimum number of constraints, i.e., obstacles, that need to be removed to connect a start to a goal location with a collis…

cs.RO2023

Computational Tradeoff in Minimum Obstacle Displacement Planning for Robot Navigation

Antony Thomas, Giulio Ferro, Fulvio Mastrogiovanni +1

In this paper, we look into the minimum obstacle displacement (MOD) planning problem from a mobile robot motion planning perspective. This problem finds an optimal path to goal by…

cs.RO2023★ 75 cited

An Ergonomic Role Allocation Framework for Dynamic Human-Robot Collaborative Tasks

Elena Merlo, Edoardo Lamon, Fabio Fusaro +4

By incorporating ergonomics principles into the task allocation processes, human-robot collaboration (HRC) frameworks can favour the prevention of work-related musculoskeletal diso…

cs.RO2022★ 5 cited

If You Are Careful, So Am I! How Robot Communicative Motions Can Influence Human Approach in a Joint Task

Linda Lastrico, Nuno Ferreira Duarte, Alessandro Carfì +4

As humans, we have a remarkable capacity for reading the characteristics of objects only by observing how another person carries them. Indeed, how we perform our actions naturally…

cs.RO2022★ 2 cited

Robots with Different Embodiments Can Express and Influence Carefulness in Object Manipulation

Linda Lastrico, Luca Garello, Francesco Rea +4

Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else. This level of communicative skills and…

cs.RO2022★ 1 cited

Gestural and Touchscreen Interaction for Human-Robot Collaboration: a Comparative Study

Antonino Bongiovanni, Alessio De Luca, Luna Gava +8

Close human-robot interaction (HRI), especially in industrial scenarios, has been vastly investigated for the advantages of combining human and robot skills. For an effective HRI,…

cs.RO2022★ 2 cited

Mixed Reality as Communication Medium for Human-Robot Collaboration

Simone Macciò, Alessandro Carfì, Fulvio Mastrogiovanni

Humans engaged in collaborative activities are naturally able to convey their intentions to teammates through multi-modal communication, which is made up of explicit and implicit c…

cs.RO2022

Minimum Displacement Motion Planning for Movable Obstacles

Antony Thomas, Fulvio Mastrogiovanni

This paper presents a minimum displacement motion planning problem wherein obstacles are displaced by a minimum amount to find a feasible path. We define a metric for robot-obstacl…

cs.RO2022★ 1 cited

Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks

Luca Garello, Linda Lastrico, Alessandra Sciutti +3

Object manipulation is a natural activity we perform every day. How humans handle objects can communicate not only the willfulness of the acting, or key aspects of the context wher…

cs.RO2021★ 13 cited

Dynamic Human-Robot Role Allocation based on Human Ergonomics Risk Prediction and Robot Actions Adaptation

Elena Merlo, Edoardo Lamon, Fabio Fusaro +5

Despite cobots have high potential in bringing several benefits in the manufacturing and logistic processes, but their rapid (re-)deployment in changing environments is still limit…