Robotic Actuation and Control of a Catheter for Structural Intervention Cardiology

Structural intervention cardiology (SIC) interventions are crucial procedures for correcting heart valves, walls, and muscle form defects. However, the possibility of embolization or perforation, as well as the lack of transparent vision and autonomous surgical equipment, make it difficult for the clinician. This paper proposes a robot-assisted tendon-driven catheter and machine learning-based path planner to overcome these challenges. Firstly, an analytical inverse kinematic model is constructed to convert the tip location in the Cartesian space to the tendons' displacement. Then inverse reinforcement learning algorithm is employed to calculate the optimal path to avoid possible collisions between the catheter tip and the atrial wall. Moreover, a closed-loop feedback controller is adopted to improve positioning accuracy in a direct distal position measurement manner. Simulation and experiments are designed and conducted to demonstrate the feasibility and performance of the proposed system.