Learning Based Sim-to-Real Autonomous 3D Navigation for Robot-Operated Right Heart Catheterization

EasyChair Preprint no. 13706

Abstract

In 2021, Cardiovascular Diseases (CVDs) were attributed to 20.5 million deaths worldwide, representing a third of all global mortality annually and positioning CVDs as the predominant cause of death. Right Heart Catheterization (RHC) has emerged as an exceptionally effective clinical procedure for diagnosing some conditions of CVDs. Concurrently, there is a burgeoning interest in harnessing machine learning (ML) and artificial intelligence (AI) technologies to interventional robots with autonomous capabilities. This study unveils a novel learning-based robotic system designed for the 3D navigation of catheters, employing Sim-to-Real transfer techniques with a particular emphasis on Right Heart Catheterization (RHC).

Keyphrases: Behavioural Cloning, Interventional Robotics, MR-compatible robotics, Right Heart Catheterization

@Booklet{EasyChair:13706,
  author = {Yaxi Wang and Vivek Muthurangu and Helge Wurdemann},
  title = {Learning Based Sim-to-Real Autonomous 3D Navigation for Robot-Operated Right Heart Catheterization},
  howpublished = {EasyChair Preprint no. 13706},

  year = {EasyChair, 2024}}