Maria Pozzi — accepted AI-conference papers

2026

Leveraging Embodied Mechanical Intelligence for Learning Decluttering Tasks

Enrico Turco, Valerio Bo, Chiara Castellani, Gionata Salvietti, Monica Malvezzi, Domenico Prattichizzo +1

ICRA 2026poster

In this work, we investigate how a state-of-the-art grasp planner based on deep reinforcement learning performs when applied to a soft-rigid gripper in a decluttering task. The gripper, called Soft ScoopGripper, is endowed with a rigid scoop-shaped part that facilitates the interaction with the envi…

Cited by 0 Scholar ↗

2025

Human-Robot Collaborative Cable-Suspended Manipulation With Contact Distinction

Giovanni Cortigiani, Monica Malvezzi, Domenico Prattichizzo, Maria Pozzi

RA-L 2025

The collaborative transportation of objects between humans and robots is a fundamental task in physical human-robot interaction. Most of the literature considers the rigid co-grasping of non-deformable items in which both the human and the robot directly hold the transported object with their hands.

Cited by 5 Source ↗Scholar ↗

2025

Soft Human-Robot Handover Using a Vision-Based Pipeline

Chiara Castellani, Enrico Turco, Valerio Bo, Monica Malvezzi, Domenico Prattichizzo, Gabriele Costante +1

RA-L 2025

Handing over objects is an essential task in human-robot collaborative scenarios. Previous studies have predominantly employed rigid grippers to perform the handover, focusing on generating grasps that avoid physical contact with people. In this paper, we present a vision-based open-palm handover so

Cited by 7 Source ↗Scholar ↗

2024

The Double-Scoop Gripper: A Tendon-Driven Soft-Rigid End-Effector for Food Handling Exploiting Constraints in Narrow Spaces

Leonardo Franco, Enrico Turco, Valerio Bo, Maria Pozzi, Monica Malvezzi, Domenico Prattichizzo +1

ICRA 2024poster

Food handling is a challenging task for robotic grippers, as it requires to manipulate highly deformable and fragile items, that can be easily damaged. Moreover, ingredients for the preparation of the different dishes are usually stored in small containers that are often not easily accessible. This…

Cited by 1 Source ↗Scholar ↗

2024

Wearable Haptics for a Marionette-inspired Teleoperation of Highly Redundant Robotic Systems

Davide Torielli, Leonardo Franco, Maria Pozzi, Luca Muratore, Monica Malvezzi, Nikos Tsagarakis +1

ICRA 2024poster

The teleoperation of complex, kinematically redundant robots with loco-manipulation capabilities represents a challenge for human operators, who have to learn how to operate the many degrees of freedom of the robot to accomplish a desired task. In this context, developing an easy-to-learn and easy-t…

Cited by 4 Source ↗Scholar ↗

2022

Automated Design of Embedded Constraints for Soft Hands Enabling New Grasp Strategies

Valerio Bo, Enrico Turco, Maria Pozzi, Monica Malvezzi, Domenico Prattichizzo

RA-L 2022

Soft robotic hands allow to fully exploit hand-object-environment interactions to complete grasping tasks. However, their usability can still be limited in some scenarios (e.g., restricted or cluttered spaces). In this article, we propose to enhance the versatility of soft grippers by adding special

Cited by 9 Source ↗Scholar ↗

2021

Grasp Planning With a Soft Reconfigurable Gripper Exploiting Embedded and Environmental Constraints

Enrico Turco, Valerio Bo, Maria Pozzi, Alessandro Rizzo, Domenico Prattichizzo

RA-L 2021

Grasping in unstructured environments requires highly adaptable and versatile hands together with strategies to exploit their features to get robust grasps. This letter presents a method to grasp objects using a novel reconfigurable soft gripper with embodied constraints, the Soft ScoopGripper (SSG)

Cited by 19 Source ↗Scholar ↗

2020

Cooperative Human-Robot Grasping With Extended Contact Patches

Sara Marullo, Maria Pozzi, Domenico Prattichizzo, Monica Malvezzi

RA-L 2020

Grasping large and heavy objects with a robot assistant is one of the most interesting scenarios in physical Human-Robot Interaction. Many solutions have been proposed in the last 40 years, focusing not only on human safety, but also on comfort and ergonomics. When carrying objects with large planar

Cited by 2 Source ↗Scholar ↗

2020

Grasping With the SoftPad, a Soft Sensorized Surface for Exploiting Environmental Constraints With Rigid Grippers

Chiara Gaudeni, Maria Pozzi, Zubair Iqbal, Monica Malvezzi, Domenico Prattichizzo

RA-L 2020

A common trend in robotic manipulation is to build compliant hands that can exploit environmental constraints to perform robust grasps. However, in large-scale industrial applications, end-effectors are mostly rigid. How can we exploit environmental constraints using rigid industrial grippers? We pr

Cited by 8 Source ↗Scholar ↗

2018

Efficient FEM-Based Simulation of Soft Robots Modeled as Kinematic Chains

Maria Pozzi, Eder Miguel, Raphael Deimel, Monica Malvezzi, Bernd Bickel, Oliver Brock +1

ICRA 2018poster

In the context of robotic manipulation and grasping, the shift from a view that is static (force closure of a single posture) and contact-deprived (only contact for force closure is allowed, everything else is obstacle) towards a view that is dynamic and contact-rich (soft manipulation) has led to a…

Cited by 50 Source ↗Scholar ↗

2018

Grasp Stiffness Control in Robotic Hands Through Coordinated Optimization of Pose and Joint Stiffness

Virginia Ruiz Garate, Maria Pozzi, Domenico Prattichizzo, Nikolaos G. Tsagarakis, Arash Ajoudani

RA-L 2018

This letter presents a novel controller for robotic hands, which regulates the grasp stiffness by manipulating the pose and the finger joint stiffness of hands with multiple degrees of freedom while guaranteeing grasp stability. The proposed approach is inspired by the observations of human motor be

Cited by 22 Source ↗Scholar ↗

2018

Operator Awareness in Human-Robot Collaboration Through Wearable Vibrotactile Feedback

Andrea Casalino, Costanza Messeri, Maria Pozzi, Andrea Maria Zanchettin, Paolo Rocco, Domenico Prattichizzo

RA-L 2018

In industrial scenarios, requiring human-robot collaboration, the understanding between the human operator and his/her robot coworker is paramount. On the one side, the robot has to detect human intentions, and on the other side, the human needs to be aware of what is happening during the collaborat

Cited by 73 Source ↗Scholar ↗

2018

The Closure Signature: A Functional Approach to Model Underactuated Compliant Robotic Hands

Maria Pozzi, Gionata Salvietti, João Bimbo, Monica Malvezzi, Domenico Prattichizzo

RA-L 2018

Underactuated and compliant hands, frequently referred to as soft hands, have been recently proposed to overcome common issues of multifingered robotic hands. Although several prototypes have been developed, there is still a lack of systematic ways to model and control these devices to get grasps ex

Cited by 22 Source ↗Scholar ↗

2017

On Grasp Quality Measures: Grasp Robustness and Contact Force Distribution in Underactuated and Compliant Robotic Hands

Maria Pozzi, Monica Malvezzi, Domenico Prattichizzo

RA-L 2017

The availability of grasp quality measures is fundamental for grasp planning and control, and also to drive designers in the definition and optimization of robotic hands. This work investigates on grasp robustness and quality indexes that can be applied to power grasps with underactuated and complia

Cited by 30 Source ↗Scholar ↗

2016

Grasp quality evaluation in underactuated robotic hands

Maria Pozzi, Ashok M. Sundaram, Monica Malvezzi, Domenico Prattichizzo, Máximo A. Roa

IROS 2016poster

Underactuated and synergy-driven hands are gaining attention in the grasping community mainly due to their simple kinematics, intrinsic compliance and versatility for grasping objects even in non structured scenarios. The evaluation of the grasping capabilities of such hands is a challenging task. T…

Cited by 13 Source ↗Scholar ↗