Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery
Ameya Pore,Davide Corsi,Enrico Marchesini,Diego Dall’Alba,Alicia Casals,Alessandro Farinelli,Paolo Fiorini,Ameya Pore,Davide Corsi,Enrico Marchesini,Diego Dall’Alba,Alicia Casals,Alessandro Farinelli,Paolo Fiorini
Deep Reinforcement Learning (DRL) is a viable solution for automating repetitive surgical subtasks due to its ability to learn complex behaviours in a dynamic environment. This task automation could lead to reduced surgeon’s cognitive workload, increased precision in critical aspects of the surgery, and fewer patient-related complications. However, current DRL methods do not guarantee any safety c...
