Wood Nathan A, Schwartzman David, Passineau Michael J, Halbreiner M Scott, Moraca Robert J, Zenati Marco A, Riviere Cameron N
The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Cardiovascular Institute, University of Pittsburgh, Pittsburgh, Pennsylvania.
Int J Med Robot. 2019 Apr;15(2):e1971. doi: 10.1002/rcs.1971. Epub 2018 Nov 29.
Organ-mounted robots adhere to the surface of a mobile organ as a platform for minimally invasive interventions, providing passive compensation of physiological motion. This approach is beneficial during surgery on the beating heart. Accurate localization in such applications requires accounting for the heartbeat and respiratory motion. Previous work has described methods for modeling quasi-periodic motion of a point and registering to a static preoperative map. The existing techniques, while accurate, require several respiratory cycles to converge.
This paper presents a general localization technique for this application, involving function approximation using radial basis function (RBF) interpolation.
In an experiment in the porcine model in vivo, the technique yields mean localization accuracy of 1.25 mm with a 95% confidence interval of 0.22 mm.
The RBF approximation provides accurate estimates of robot location instantaneously.
器官挂载式机器人附着在可移动器官表面，作为微创干预的平台，可对生理运动进行被动补偿。这种方法在心脏跳动时进行手术时很有帮助。在此类应用中，精确的定位需要考虑心跳和呼吸运动。先前的工作已经描述了用于对点的准周期运动进行建模并注册到静态术前地图的方法。现有技术虽然准确，但需要几个呼吸周期才能收敛。
本文提出了一种适用于此应用的通用定位技术，涉及使用径向基函数（RBF）插值进行函数逼近。
在猪体内模型实验中，该技术的平均定位精度为1.25毫米，95%置信区间为0.22毫米。
RBF逼近可即时提供机器人位置的准确估计。
