The workshop will explore emerging methods and technologies for enhancing the rise of the next-generation of training and assistance systems for robotic surgery, integrating Artificial Intelligence (AI) for augmented perception and cognitive capabilities and advanced control methods for the generation of safe, reliable, and accurate robot motions. It will be organised according to following sections:
- Medical Knowledge: this section will introduce the surgery challenges that benefit from the integration of emerging AI/robotics methods and technologies. It will further discuss how to model medical knowledge into a formal representation, understandable by both humans and robot, with the aim of laying foundations for designing effective tools for training and assistance in robotic surgery.
- AI for scene understanding. In this section the latest advances in AI algorithms for scene understanding will be explored, particularly focusing on the design of cognitive architecture for intelligent assistive systems able to perform reasoning and make decisions.
- Robot Control: this section will discuss how high-level commands can be mapped and executed by the low-level robot control architecture, coping with strict requirements such as accuracy, safe interaction, and collision avoidance.
- Use cases and applications: as a use-case example of the previously discussed topics, it will be presented the results obtained in the recently-concluded H2020 project Smart Autonomous Robotic Assistant Surgeon (SARAS https://saras-project.eu). A Further prototype application on Percutaneous Nephrolithotripsy with robotic assistance will be presented.
|08:30||Registration & Coffee|
|09:00||Opening: Welcome & Introduction||Federica Ferraguti|
|09:05||Robotic Surgery in Urology||Stefano Puliatti|
|09:25||Robotic Training in the age of Digital Surgery||Kyle Lam|
|AI for scene understanding|
|09:45||Surgical Data Science for Trustworthy Decision Support and Context Awareness||Sara Moccia|
|10:05||AI assisted surgical scene and error understanding||Pieter De Backer|
|11:00||Surgical Robots: from 3D Vision to Virtual Reality||Alicia Casals|
|11:25||Safe Motion Generation for Assistive Surgical Robots||Marcello Bonfe|
|Use Cases and Applications|
|11:45||AI and Robotics for Better Surgery: Lesson Learned in three EU projects||Riccardo Muradore|
|12:05||Augmented Reality and Robotic Assistance for Training: the PCNL use case||Saverio Farsoni|
|12:25||Closing Remarks||Federica Ferraguti|
The attendees will be given a comprehensive overview about the recent advances and future perspectives in robotic surgery training and assistance systems. They will learn fundamental tools to cope with the problem of modeling medical knowledge to create a formal representation of the expert know-how, understandable and transferrable to both humans and robots.
The attendees will explore the most advanced state-of-art methods for designing the next generation of cognitive AI systems, with perception and reasoning capabilities, that will be able to support surgeons during training and surgery procedures. Furthermore, the participants will familiarise themselves with the technical aspects related to the design of the control architectures that allow the execution of safe, reliable, and accurate robot motions in the cluttered and dynamic environment of the surgical scene.
The attendees will have the opportunity to fix the discussed concepts by attending the presentation of the results of the SARAS project and further related use cases. Finally, the speakers will be available to answer audience questions and inspiring discussions.
Dr. Saverio Farsoni, University of Ferrara
Dr. Federica Ferraguti, University of Modena and Reggio Emilia
Prof. Marcello Bonfè, Univeristy of Ferrara
HALF DAY WORKSHOP – AM
This workshop is accredited for 3 CPD points.