GA3C Reinforcement Learning for Surgical Steerable Catheter Path Planning
Alice Segato,Luca Sestini,Antonella Castellano,Elena De Momi,Alice Segato,Luca Sestini,Antonella Castellano,Elena De Momi
Path planning algorithms for steerable catheters, must guarantee anatomical obstacles avoidance, reduce the insertion length and ensure the compliance with needle kinematics. The majority of the solutions in literature focuses on graph based or sampling based methods, both limited by the impossibility to directly obtain smooth trajectories. In this work we formulate the path planning problem as a ...
