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Organ‐mounted robot localization via function approximation
Author(s) -
Wood Nathan A.,
Schwartzman David,
Passineau Michael J.,
Halbreiner M. Scott,
Moraca Robert J.,
Zenati Marco A.,
Riviere Cameron N.
Publication year - 2019
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1971
Subject(s) - computer science , heartbeat , interpolation (computer graphics) , robot , artificial intelligence , radial basis function , mobile robot , computer vision , motion (physics) , algorithm , computer security , artificial neural network
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.