Pose State Perception of Interventional Robot for Cardio-cerebrovascular Procedures
Journal:
arXiv
Published Date:
Jun 17, 2025
Abstract
In response to the increasing demand for cardiocerebrovascular interventional
surgeries, precise control of interventional robots has become increasingly
important. Within these complex vascular scenarios, the accurate and reliable
perception of the pose state for interventional robots is particularly crucial.
This paper presents a novel vision-based approach without the need of
additional sensors or markers. The core of this paper's method consists of a
three-part framework: firstly, a dual-head multitask U-Net model for
simultaneous vessel segment and interventional robot detection; secondly, an
advanced algorithm for skeleton extraction and optimization; and finally, a
comprehensive pose state perception system based on geometric features is
implemented to accurately identify the robot's pose state and provide
strategies for subsequent control. The experimental results demonstrate the
proposed method's high reliability and accuracy in trajectory tracking and pose
state perception.
