73 citations · 91 across the 4 of their papers we have counts for
5 papers
Sim-To-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery
Paul Maria Scheikl, Eleonora Tagliabue, Balázs Gyenes +4
Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement lea…
Deliberation in autonomous robotic surgery: a framework for handling anatomical uncertainty
Eleonora Tagliabue, Daniele Meli, Diego Dall'Alba +1
Autonomous robotic surgery requires deliberation, i.e. the ability to plan and execute a task adapting to uncertain and dynamic environments. Uncertainty in the surgical domain is…
Learning from Demonstrations for Autonomous Soft-tissue Retraction
Ameya Pore, Eleonora Tagliabue, Marco Piccinelli +3
The current research focus in Robot-Assisted Minimally Invasive Surgery (RAMIS) is directed towards increasing the level of robot autonomy, to place surgeons in a supervisory posit…
Autonomous tissue retraction with a biomechanically informed logic based framework
D. Meli, E. Tagliabue, D. Dall'Alba +1
Autonomy in robot-assisted surgery is essential to reduce surgeons' cognitive load and eventually improve the overall surgical outcome. A key requirement for autonomy in a safety-c…
Robotic needle steering in deformable tissues with extreme learning machines
Pedro Henrique Suruagy Perrusi, Anna Cazzaniga, Paul Baksic +3
Control strategies for robotic needle steering in soft tissues must account for complex interactions between the needle and the tissue to achieve accurate needle tip positioning. R…