Towards Autonomous Robotic Surgery

Paolo Fiorini (Editor)

ISBN: 9783032042460
Published: 5 April 2026
Format: Hardcover
Pages: XVIII, 318
Language: English
Publisher: Springer

Description

This book presents the complete results of the European Research Council Advanced Grant project ARS (Autonomous Robotic Surgery), funded under Horizon 2020 (ERC-ADG N. 742671). It documents the development and validation of methods to integrate autonomous capabilities into robotic surgery, merging robotics with artificial intelligence in the challenging domain of robot-assisted surgical procedures. Leveraging the da Vinci Research Kit (dVRK), the research spans knowledge representation, medical image processing, software engineering, robotic control, human-machine interfaces, haptics, and tele-robotics. Each chapter summarizes key doctoral dissertations produced during the project, offering a coherent and accessible overview unavailable from individual publications.

Key Features

Comprehensive documentation of the ERC-funded ARS project outcomes, from foundational AI methods to real-world surgical robotics validation. Covers the full pipeline of autonomous robotic surgery: knowledge extraction, task planning, situation awareness, simulation, plan execution, and hardware design. Addresses ethical, social, and communication dimensions of surgical autonomy. Presents practical methods validated with the da Vinci Research Kit (dVRK). Includes both technical contributions and non-technical perspectives on deploying autonomous systems in clinical settings.

Coverage

The book is organized into three major parts across 16 chapters. Part I — Knowledge Extraction, Representation and Task Planning — covers learning surgical procedures from text, surgical task planning and learning, gesture learning from data, and simulation-based autonomy. Part II — Plan Instantiation, Simulation and Execution — addresses situation awareness in autonomous surgical robots (calibration and Medical SLAM), cognitive architecture, autonomous tissue retraction with DEFRAS, learning tissue retraction in simulation, and new hardware design and analysis. Part III — The Non-technical Issues of Autonomy — explores ethical and social dimensions, automation at the boundary of autonomy, communication strategy, and exploitation of results.

About the Editor

Paolo Fiorini is Professor at the Department of Computer Science, University of Verona, Italy. He was the Principal Investigator of the ERC Advanced Grant project ARS (Autonomous Robotic Surgery). His research focuses on robotics, autonomous systems, and their applications in minimally invasive surgery.

Table of Contents

1. Introduction — Paolo Fiorini
Part I: Knowledge Extraction, Representation and Task Planning
2. Learning Surgical Procedures from Text — Marco Bombieri
3. Surgical Task Planning and Learning — Daniele Meli
4. Towards Surgical Task Planning from Text — Marco Bombieri
5. Learning Surgical Gestures from Data — Michele Ginesi
6. Simulation and Autonomy — Eleonora Tagliabue
Part II: Plan Instantiation, Simulation and Execution
7. Situation Awareness in Autonomous Surgical Robots: Calibration and Medical SLAM — Andrea Roberti
8. The Cognitive Architecture — Eleonora Tagliabue, Marco Bombieri
9. Autonomous Tissue Retraction with DEFRAS — Eleonora Tagliabue
10. Learning Tissue Retraction in Simulation — Eleonora Tagliabue
11. New Hardware: Design, Models and Analysis — Andrea Calanca, Zhuoqi Cheng, Diego Dall'Alba, Paolo Fiorini, Giovanni Gerardo Muscolo, Chiara Zandoná
Part III: The Non-technical Issues of Autonomy
12. The Ethical and Social Aspects of Autonomy — Sara Patuzzo Manzati
13. Automation on the Brink of Autonomy: Letting Go of Control — Maria-Camilla Fiazza, Paolo Fiorini
14. Communication Strategy of the ARS Project — Martina Doppio, Paolo Fiorini
15. The Exploitation of Results — Paolo Fiorini, Bogdan Maris
16. Conclusions — Paolo Fiorini, Marco Bombieri

Why Buy This Book?

This is the definitive reference on the ARS project — the only work that consolidates six years of European-funded research on autonomous robotic surgery into a single, coherent volume. Essential for researchers, engineers, and clinicians working at the intersection of AI, robotics, and surgery. Valuable for medical technology developers, biomedical engineers, and policymakers navigating the regulatory and ethical landscape of autonomous surgical systems. A critical resource for graduate students and doctoral researchers entering the field of surgical robotics.

Keywords

Autonomous Robotic Surgery, Artificial Intelligence in Surgery, Surgical Robotics, Robot-Assisted Surgery, Knowledge Representation, Medical SLAM, da Vinci Research Kit, Haptics, Tele-Robotics, Surgical Task Planning, Tissue Retraction, Embodied AI, ERC Advanced Grant, Biomedical Engineering

Target Audience

Robotics Researchers, Biomedical Engineers, Surgical Robotics Developers, AI and Machine Learning Researchers, Medical Technology Professionals, Graduate Students in Robotics and Computer Science, University Libraries, Hospital Libraries, Research Institutions

Genre

Robotics, Artificial Intelligence, Biomedical Engineering, Surgical Technology, Medical Robotics

Q&A

What were the main outcomes of the ERC ARS project on autonomous robotic surgery?
The ARS project developed practical methods to integrate robotics and artificial intelligence for autonomous functions in robot-assisted surgery, spanning knowledge extraction, task planning, gesture learning, situation awareness, tissue retraction, and new hardware design, all validated using the da Vinci Research Kit.

How does autonomous robotic surgery differ from conventional robot-assisted surgery?
Conventional robot-assisted surgery relies on continuous human teleoperation, while autonomous robotic surgery aims to delegate specific tasks — such as tissue retraction, suturing, or instrument positioning — to AI-driven systems that can plan and execute actions with minimal human intervention.

What role does the da Vinci Research Kit play in surgical robotics research?
The da Vinci Research Kit (dVRK) is an open-source research platform that enables researchers to develop and test autonomous surgical functions across multiple domains including robotic control, medical image processing, haptics, and human-machine interfaces.

What are the ethical considerations of autonomous surgical robots?
Key ethical considerations include questions of liability and accountability when surgical decisions are delegated to machines, patient informed consent for AI-driven procedures, the boundaries between automation and autonomy, and ensuring equitable access to advanced surgical technologies.

What is Medical SLAM and how is it used in surgical robotics?
Medical SLAM (Simultaneous Localization and Mapping) enables surgical robots to build real-time 3D maps of the surgical environment while tracking instrument positions, providing the spatial awareness essential for autonomous task execution during minimally invasive procedures.

How are surgical task planning and knowledge representation used in autonomous surgery?
Surgical task planning uses AI techniques such as answer set programming and natural language processing to extract procedural knowledge from surgical textbooks, represent it formally, and generate executable plans that autonomous robots can follow during surgical procedures.

What is the significance of tissue retraction automation in robotic surgery?
Automated tissue retraction is a critical subtask in minimally invasive surgery that involves manipulating soft tissue to expose the surgical site. Automating this function frees the surgeon to focus on the primary procedure and reduces the need for additional operating room staff.

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