A Sensor-Less Guider Contact Force Estimation Approach for Endovascular Slender Robot-Assisted Guidance System

摘要

The objective of this study is to propose and validate a contact force estimation method based on guider shape prediction, aiming at estimating the contact force between the distal end of the guider and the vascular wall. A guider prediction algorithm is developed to simulate the stable shape of different contact points within a phantom model. Subsequently, a shape-contact force model is established, and the contact force is estimated based on the parametric equation of the guider shape. A suspended force measuring platform is developed to validate the contact force estimation approach. Additionally, the influence of contact position and guider stiffness on contact force is analyzed. The average accuracy of contact force estimation is 91.17%. The average relative error of the guider shape is 2.5%, with a maximum offset error of 4.6 mm. During the contact force estimation experiment, the maximum relative error of the contact force is 19.83%, and the force deviation is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.6\times 10^{-2}$ </tex-math></inline-formula> N. For nitinol 0.4 mm at contact point 1, the relative error of the contact force is 11.58%, with a force deviation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.0\times 10^{-3}$ </tex-math></inline-formula> N. The estimated contact force aligns well with the measured force, demonstrating the feasibility of the proposed contact force estimation method. This study establishes a sensor-less contact force estimation method for vascular interventional robot guidance systems, offering insights into improving the robot’s ability to navigate narrow blood vessels. The analysis of contact force provides both theoretical and experimental foundations for the design and application of vascular interventional robot guidance systems.