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Eleonora Tagliabue

11 accepted papers

2026

A Shared Control Architecture for Vitreoretinal Surgery With Safety Guarantee Using Control Barrier Functions

Nicola Piccinelli, Federico Vesentini, Marius Briel, Ludwig Haide, Eleonora Tagliabue, Marco Pellegrini +2
RA-L 2026

Control Barrier Functions (CBFs) provide a powerful framework for enforcing real-time safety in control systems and have seen increasing applications in safety-critical domains, such as surgical robotics. In vitreoretinal microsurgery, where precision and tissue protection are crucial, we propose a

Cited by 0Source ↗Scholar ↗
2026

A Shared Control Architecture for Vitreoretinal Surgery with Safety Guarantee Using Control Barrier Functions

Nicola Piccinelli, Federico Vesentini, Marius Briel, Ludwig Haide, Eleonora Tagliabue, Marco Pellegrini +2
ICRA 2026poster

Control Barrier Functions (CBFs) provide a powerful framework for enforcing real-time safety in control systems and have seen increasing applications in safety-critical domains, such as surgical robotics. In vitreoretinal microsurgery, where precision and tissue protection are crucial, we propose a …

Cited by 0Source ↗Scholar ↗
2026

Automated Retinal Photocoagulation Using Instrument-Integrated OCT and Laser Pattern Mapping

Marius Briel, Ludwig Haide, Dongyue Wu, Justus Hornstein, Philipp Matten, Nicola Piccinelli +3
ICRA 2026poster

Retinal endolaser photocoagulation (REPC) is a repetitive intraocular surgical procedure that could greatly benefit from automation and distance-based control, improving both efficiency and safety. This work presents a robotic system designed for automated REPC, utilizing instrument-integrated optic…

Cited by 0Scholar ↗
2026

Distance-Based Shared Control for Vitreoretinal Surgery

Marius Briel, Dongyue Wu, Maximilian Hess, Ludwig Haide, Nicola Piccinelli, Gernot Kronreif +3
RA-L 2026

The fragility of ocular tissues combined with the limited surgical workspace demands precise instrument control and focus, making sensor-integrated robotic systems a promising solution. In this paper, we introduce a surgical system for telemanipulated endolaser photocoagulation that leverages instru

Cited by 0Source ↗Scholar ↗
2026

Distance-Based Shared Control for Vitreoretinal Surgery

Marius Briel, Dongyue Wu, Maximilian Hess, Ludwig Haide, Nicola Piccinelli, Gernot Kronreif +3
ICRA 2026poster

The fragility of ocular tissues combined with the limited surgical workspace demands precise instrument control and focus, making sensor-integrated robotic systems a promising solution. In this paper, we introduce a surgical system for telemanipulated endolaser photocoagulation that leverages instru…

Cited by 0Source ↗Scholar ↗
2024

Lens Capsule Tearing in Cataract Surgery using Reinforcement Learning

Rebekka Charlotte Peter, Steffen Peikert, Ludwig Haide, Doan Xuan Viet Pham, Tahar Chettaoui, Eleonora Tagliabue +5
ICRA 2024poster

Cataract is the leading cause of blindness worldwide with an increasing number of patients due to changing demographics, making automation an important part in future surgical treatment. In this work, we focus on a substep of cataract surgery, the Continuous Curvilinear Capsulorhexis (CCC). With a h…

Cited by 0Source ↗Scholar ↗
2023

Autonomous Robotic System for Breast Biopsy With Deformation Compensation

Sandro Ferrari, Eleonora Tagliabue, Bogdan Mihai Maris, Paolo Fiorini
RA-L 2023

Image-guided biopsy is the most common technique for breast cancer diagnosis. Although magnetic resonance imaging (MRI) has the highest sensitivity in breast lesion detection, ultrasound (US) biopsy guidance is generally preferred due to its non-invasiveness and real-time image feedback during the i

Cited by 10Source ↗Scholar ↗
2023

Sim-to-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery

Paul Maria Scheikl, Eleonora Tagliabue, Balázs Gyenes, Martin Wagner, Diego Dall'Alba, Paolo Fiorini +1
RA-L 2023

Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement learning has shown promising results in learning complex visuomotor policies, especially in simulation environments where m

Cited by 82Source ↗Scholar ↗
2022

Deliberation in autonomous robotic surgery: a framework for handling anatomical uncertainty

Eleonora Tagliabue, Daniele Meli, Diego Dall'Alba, Paolo Fiorini
ICRA 2022poster

Autonomous robotic surgery requires deliberation, i.e. the ability to plan and execute a task adapting to uncer-tain and dynamic environments. Uncertainty in the surgical domain is mainly related to the partial pre-operative knowledge about patient-specific anatomical properties. In this paper, we i…

Cited by 17Source ↗code ↗Scholar ↗
2021

Data-Driven Intra-Operative Estimation of Anatomical Attachments for Autonomous Tissue Dissection

Eleonora Tagliabue, Diego Dall'Alba, Micha Pfeiffer, Marco Piccinelli, Riccardo Marin, Umberto Castellani +2
RA-L 2021

The execution of surgical tasks by an Autonomous Robotic System (ARS) requires an up-to-date model of the current surgical environment, which has to be deduced from measurements collected during task execution. In this work, we propose to automate tissue dissection tasks by introducing a convolution

Cited by 18Source ↗Scholar ↗
2020

Soft Tissue Simulation Environment to Learn Manipulation Tasks in Autonomous Robotic Surgery

Eleonora Tagliabue, Ameya Pore, Diego Dall’Alba, Enrico Magnabosco, Marco Piccinelli, Paolo Fiorini
IROS 2020poster

Reinforcement Learning (RL) methods have demonstrated promising results for the automation of subtasks in surgical robotic systems. Since many trial and error attempts are required to learn the optimal control policy, RL agent training can be performed in simulation and the learned behavior can be t…

Cited by 65Source ↗Scholar ↗