Organ-mounted robot localization via function approximation

Nathan A. Wood, David Schwartzman, Michael J. Passineau, M. Scott Halbreiner, Robert J. Moraca, Marco A. Zenati and Cameron N. Riviere
Journal Article, International Journal of Medical Robotics and Computer Assisted Surgery, pp. e1971, November, 2018

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Background: 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.

Methods: This paper presents a general localization technique for this application, involving function approximation using radial basis function (RBF) interpolation.

Results: 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.

Conclusions: The RBF approximation provides accurate estimates of robot location instantaneously.

author = {Nathan A. Wood and David Schwartzman and Michael J. Passineau and M. Scott Halbreiner and Robert J. Moraca and Marco A. Zenati and Cameron N. Riviere},
title = {Organ-mounted robot localization via function approximation},
journal = {International Journal of Medical Robotics and Computer Assisted Surgery},
year = {2018},
month = {November},
pages = {e1971},
keywords = {medical robotics, cardiac surgery, physiological motion compensation},
} 2018-12-12T08:03:16-04:00