Probabilistic Kinematic Model of a Robotic Catheter for 3D Position Control

Abstract

Continuum robots offer compliant and dexterous operations, which are suitable to be used in unstructured environments. Tendon-driven catheters, owing to their continuum structure, are applied in minimal invasive surgeries such as intracardiac interventions. However, due to the intrinsic nonlinearities and external disturbances, it is still a challenging task to accurately steer the catheter tip to the desired 3D positions. In this article, we proposed a new probabilistic kinematic model and a model-based three-dimensional position control scheme for a tendon-driven cardiac catheter. A dynamic Gaussian-based probabilistic model is developed to learn a mapping from the catheter states to the control actions. Based on the probabilistic model, a closed-loop position control is developed, in which the catheter is driven by a newly designed catheter driver system and tracked by a multiple near-infrared camera system. The proposed catheter framework is evaluated by the 3D trajectory tracking experiments both in a real 3D open space and in a minimum-energy-based simulator. The proposed control framework approximates the general kinematic by a combination of a catheter translation model and a distal workspace model, which provides the ability of automatically positioning the catheter tip in 3D and improving the accuracy by compensating the learned nonlinear effects.