Vision-based intraoperative shape sensing of concentric tube robots
作者： Alessandro Vandini , Christos Bergeles , Fang-Yu Lin , Guang-Zhong Yang
DOI: 10.1109/IROS.2015.7353732
关键词:
摘要: Concentric tube robots have shown promise for minimally invasive surgical (MIS) tasks that require navigation via tortuous anatomical paths. Despite extensive research on their kinematic and dynamic modelling, however, inaccuracies deformations of shape due to unknown loads collisions with the anatomy make intraoperative sensing a requirement. This paper presents vision-based shape-sensing algorithm concentric robots. The proposed fuses information extracted from standard imaging modality, monoplane X-ray fluoroscopy, kinematics model robot, achieve automatic, real-time, accurate continuous robot-shape estimations despite kinematics' noise unmodelled forces. Fusion is performed by fast 2D/3D non-rigid registration, which combines tracking robot. Extensive simulations range models virtual acting experimental evaluation in air skull phantom, demonstrate clinical value technique1.
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