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Matteo Bianchi

26 accepted papers

2026

Shear-Based Grasp Control for Multi-Fingered Underactuated Tactile Robotic Hands

Christopher Ford, Haoran Li, Manuel Giuseppe Catalano, Matteo Bianchi, Efi Psomopoulou, Nathan Lepora
ICRA 2026poster

This paper presents a shear-based control scheme for grasping and manipulating delicate objects with a Pisa/IIT anthropomorphic SoftHand equipped with soft biomimetic tactile sensors on all five fingertips. These `microTac' tactile sensors are miniature versions of the TacTip vision-based tactile se…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Benchmarking Multi-Object Grasping

Tianze Chen, Ricardo Frumento, Giulia Pagnanelli, Gianmarco Cei, Villa Keth, Shahaddin Gafarov +6
RA-L 2025

In this work, we describe a multi-object grasping benchmark to evaluate the grasping and manipulation capabilities of robotic systems in both pile and surface scenarios. The benchmark introduces three robot multi-object grasping benchmarking protocols designed to challenge different aspects of robot

Cited by 3Source ↗Scholar ↗
2025

Data-Driven Compliance Discrimination via Biomimetic Soft Optical Tactile Sensors: Implementation and Benchmarking With a Model-Based Approach

Paolo Susini, Giulia Pagnanelli, Saekwang Nam, Nathan F. Lepora, Matteo Bianchi
RA-L 2025

Humans can easily manipulate soft, deformable objects, relying on the intrinsic deformability of their fingerpads and their capabilities to infer item compliance. Transferring these skills into robotic systems is still an open challenging task. Recently, the introduction of soft biomimetic tactile s

Cited by 2Source ↗Scholar ↗
2024

Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification

Matteo Bianchi, Antonio De Santis, Andrea Tocchetti, Marco Brambilla
IJCAI 2024poster

Transparency and explainability in image classification are essential for establishing trust in machine learning models and detecting biases and errors. State-of-the-art explainability methods generate saliency maps to show where a specific class is identified, without providing a detailed explanati…

Cited by 3Source ↗PDF ↗code ↗Scholar ↗
2024

Prosthetic Upper-Limb Sensory Enhancement (PULSE): a Dual Haptic Feedback Device in a Prosthetic Socket

Alessia Silvia Ivani, Federica Barontini, Manuel G. Catalano, Giorgio Grioli, Matteo Bianchi, Antonio Bicchi
ICRA 2024poster

This study presents the Prosthetic Upper-Limb Sensory Enhancement (PULSE), a novel dual feedback device completely integrated into a prosthetic socket. The core of the system includes two compact vibrotactile actuators and two silicone chambers in contact with the user’s skin. These components provi…

Cited by 0Source ↗Scholar ↗
2023

Model-Based Compliance Discrimination via Soft Tactile Optical Sensing and Optical Flow Computation: A Biomimetic Approach

Giulia Pagnanelli, Simone Ciotti, Nathan F. Lepora, Antonio Bicchi, Matteo Bianchi
RA-L 2023

Soft tactile optical sensors have opened up new possibilities for endowing artificial robotic hands with advanced touch-related properties; however, their use for compliance discrimination has been poorly investigated and mainly relies on data-driven methods. Discrimination of object compliance is c

Cited by 5Source ↗Scholar ↗
2023

Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks

Christopher J. Ford, Haoran Li, John Lloyd, Manuel G. Catalano, Matteo Bianchi, Efi Psomopoulou +1
ICRA 2023poster

This paper presents a control scheme for force sensitive, gentle grasping with a Pisa/IIT anthropomorphic SoftHand equipped with a miniaturised version of the TacTip optical tactile sensor on all five fingertips. The tactile sensors provide high-resolution information about a grasp and how the finge…

Cited by 10Source ↗Scholar ↗
2022

BRL/Pisa/IIT SoftHand: A Low-Cost, 3D-Printed, Underactuated, Tendon-Driven Hand With Soft and Adaptive Synergies

Haoran Li, Christopher J. Ford, Matteo Bianchi, Manuel G. Catalano, Efi Psomopoulou, Nathan F. Lepora
RA-L 2022

This letter introduces the BRL/Pisa/IIT (BPI) SoftHand: a single actuator-driven, low-cost, 3D-printed, tendon-driven, underactuated robot hand that can be used to perform a range of grasping tasks. Based on the adaptive synergies of the Pisa/IIT SoftHand, we design a new joint system and tendon rou

Cited by 37Source ↗Scholar ↗
2022

Learning With Few Examples the Semantic Description of Novel Human-Inspired Grasp Strategies From RGB Data

Lorenzo Collodi, Davide Bacciu, Matteo Bianchi, Giuseppe Averta
RA-L 2022

Data-driven approaches and human inspiration are fundamental to endow robotic manipulators with advanced autonomous grasping capabilities. However, to capitalize upon these two pillars, several aspects need to be considered, which include the number of human examples used for training; the need for

Cited by 4Source ↗Scholar ↗
2021

Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands

Nathan F. Lepora, Chris Ford, Andrew Stinchcombe, Alfred Brown, John Lloyd, Manuel G. Catalano +2
ICRA 2021poster

In this work, we report on how a sense of touch can be used to control an underactuated anthropomorphic robot hand, based on an integration that respects the hand’s mechanical functionality. Our focus is on integrating the sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot…

Cited by 29Source ↗Scholar ↗
2021

Understanding Human Manipulation With the Environment: A Novel Taxonomy for Video Labelling

Visar Arapi, Cosimo Della Santina, Giuseppe Averta, Antonio Bicchi, Matteo Bianchi
RA-L 2021

In recent years, the spread of data-driven approaches for robotic grasp synthesis has come with the increasing need for reliable datasets, which can be built e.g. through video labelling. To this goal, it is important to define suitable rules to characterize the main human grasp types, for easily id

Cited by 11Source ↗Scholar ↗
2021

Wearable Integrated Soft Haptics in a Prosthetic Socket

Federica Barontini, Manuel G. Catalano, Giorgio Grioli, Matteo Bianchi, Antonio Bicchi
RA-L 2021

Modern active prostheses can be used to recover part of the motor function associated with the loss of a hand. Nevertheless, most sensory abilities are lost, and the person has to manage interaction by relying mostly on visual feedback. Despite intensive research devoted to convey touch related cues

Cited by 11Source ↗Scholar ↗
2020

A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand

Benjamin Ward-Cherrier, Jörg Conradt, Manuel G. Catalano, Matteo Bianchi, Nathan F. Lepora
IROS 2020poster

Restoring tactile sensation is essential to enable in-hand manipulation and the smooth, natural control of upper-limb prosthetic devices. Here we present a platform to contribute to that long-term vision, combining an anthropomorphic robot hand (QB SoftHand) with a neuromorphic optical tactile senso…

Cited by 19Source ↗Scholar ↗
2020

A technical framework for human-like motion generation with autonomous anthropomorphic redundant manipulators

Giuseppe Averta, Danilo Caporale, Cosimo Della Santina, Antonio Bicchi, Matteo Bianchi
ICRA 2020poster

The need for users' safety and technology accept-ability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions. Classic sol…

Cited by 15Source ↗Scholar ↗
2020

Grasp It Like a Pro: Grasp of Unknown Objects With Robotic Hands Based on Skilled Human Expertise

Chiara Gabellieri, Manolo Garabini, Franco Angelini, Visar Arapi, Alessandro Palleschi, Manuel G. Catalano +4
RA-L 2020

This work proposes a method to grasp unknown objects with robotic hands based on demonstrations by a skilled human operator. Not only are humans efficacious at grasping with their own hands but are also capable of grasping objects using robotic hands. Therefore, we consider how the grasping skills o

Cited by 39Source ↗Scholar ↗
2019

A Novel Skin-Stretch Haptic Device for Intuitive Control of Robotic Prostheses and Avatars

Nicoletta Colella, Matteo Bianchi, Giorgio Grioli, Antonio Bicchi, Manuel G. Catalano
RA-L 2019

Without proprioception, i.e., the intrinsic capability of a body to perceive its own limb position, completing daily life activities would require constant visual attention and it would be challenging or even impossible. This situation is similar to the one experienced after limb amputation and in r

Cited by 33Source ↗Scholar ↗
2019

Learning From Humans How to Grasp: A Data-Driven Architecture for Autonomous Grasping With Anthropomorphic Soft Hands

Cosimo Della Santina, Visar Arapi, Giuseppe Averta, Francesca Damiani, Gaia Fiore, Alessandro Settimi +4
RA-L 2019

Soft hands are robotic systems that embed compliant elements in their mechanical design. This enables an effective adaptation with the items and the environment, and ultimately, an increase in their grasping performance. These hands come with clear advantages in terms of ease-to-use and robustness i

Cited by 69Source ↗Scholar ↗
2019

On the role of wearable haptics for force feedback in teleimpedance control for dual-arm robotic teleoperation

Janelle P. Clark, Gianluca Lentini, Federica Barontini, Manuel G. Catalano, Matteo Bianchi, Marcia K. O’Malley
ICRA 2019poster

Robotic teleoperation enables humans to safely complete exploratory procedures in remote locations for applications such as deep sea exploration or building assessments following natural disasters. Successful task completion requires meaningful dual arm robotic coordination and proper understanding…

Cited by 44Source ↗Scholar ↗
2019

Relaying the High-Frequency Contents of Tactile Feedback to Robotic Prosthesis Users: Design, Filtering, Implementation, and Validation

Simone Fani, Katia Di Blasio, Matteo Bianchi, Manuel G. Catalano, Giorgio Grioli, Antonio Bicchi
RA-L 2019

It is known that high-frequency tactile information conveys useful cues to discriminate important contact properties for manipulation, such as first contact and roughness. Despite this, no practical system, implementing a modality matching paradigm, has been developed so far to convey this informati

Cited by 19Source ↗Scholar ↗
2019

Soft tactile sensing: retrieving force, torque and contact point information from deformable surfaces

Simone Ciotti, Teng Sun, Edoardo Battaglia, Antonio Bicchi, Hongbin Liu, Matteo Bianchi
ICRA 2019poster

Intrinsic Tactile Sensing (ITS) is a well-established technique, relying on force/torque and geometric surface description to find contact centroids. The method works well for rigid surfaces. However, finding a solution for deformable surfaces is an open issue. This work presents two solutions to ex…

Cited by 10Source ↗Scholar ↗
2018

Efficient Walking Gait Generation via Principal Component Representation of Optimal Trajectories: Application to a Planar Biped Robot With Elastic Joints

Gian Maria Gasparri, Silvia Manara, Danilo Caporale, Giuseppe Averta, Manuel Bonilla, Hamal Marino +5
RA-L 2018

Recently, the method of choice to exploit robot dynamics for efficient walking is numerical optimization (NO). The main drawback in NO is the computational complexity, which strongly affects the time demand of the solution. Several strategies can be used to make the optimization more treatable and t

Cited by 22Source ↗Scholar ↗
2018

ExoSense: Measuring Manipulation in a Wearable Manner

Edoardo Battaglia, Manuel G. Catalano, Giorgio Grioli, Matteo Bianchi, Antonio Bicchi
ICRA 2018poster

Grasp and manipulation is a complex task, deceivingly simple to accomplish for humans in everyday life, yet challenging to implement in a robotic hand. There is a trend in literature to use information obtained from studies on human grasp for the design and control of robotic manipulators. However,…

Cited by 8Source ↗Scholar ↗
2018

Incrementality and Hierarchies in the Enrollment of Multiple Synergies for Grasp Planning

Giuseppe Averta, Franco Angelini, Manuel Bonilla, Matteo Bianchi, Antonio Bicchi
RA-L 2018

Postural hand synergies or eigenpostures are joint angle covariation patterns observed in common grasping tasks. A typical definition associates the geometry of synergy vectors and their hierarchy (relative statistical weight) with the principal component analysis of an experimental covariance matri

Cited by 20Source ↗Scholar ↗
2018

Touch-Based Grasp Primitives for Soft Hands: Applications to Human-to-Robot Handover Tasks and Beyond

Matteo Bianchi, Giuseppe Averta, Edoardo Battaglia, Carlos Rosales, Manuel Bonilla, Alessandro Tondo +5
ICRA 2018poster

Recently, the avenue of adaptable, soft robotic hands has opened simplified opportunities to grasp different items; however, the potential of soft end effectors (SEEs) is still largely unexplored, especially in human-robot interaction. In this paper, we propose, for the first time, a simple touch-ba…

Cited by 29Source ↗Scholar ↗
2017

Design of an under-actuated wrist based on adaptive synergies

Simona Casini, Vinicio Tincani, Giuseppe Averta, Mattia Poggiani, Cosimo Della Santina, Edoardo Battaglia +4
ICRA 2017poster

An effective robotic wrist represents a key enabling element in robotic manipulation, especially in prosthetics. In this paper, we propose an under-actuated wrist system, which is also adaptable and allows to implement different under-actuation schemes. Our approach leverages upon the idea of soft s…

Cited by 23Source ↗Scholar ↗
2015

Design and realization of the CUFF - clenching upper-limb force feedback wearable device for distributed mechano-tactile stimulation of normal and tangential skin forces

Simona Casini, Matteo Morvidoni, Matteo Bianchi, Manuel Catalano, Giorgio Grioli, Antonio Bicchi
IROS 2015poster

Rendering forces to the user is one of the main goals of haptic technology. While most force-feedback interfaces are robotic manipulators, attached to a fixed frame and designed to exert forces on the users while being moved, more recent haptic research introduced two novel important ideas. On one s…

Cited by 155Source ↗Scholar ↗