Digital Surgery Systems, Inc.

Michael Larkin

Stephen C Minne

Alan Fridman

George C Polchin

Hossein Faraji

Systems and methods are disclosed for an automated touchless registration of patient anatomy for surgical navigation systems. An example method includes: acquiring a plurality of images of the patient; determining relevant objects from a plurality of poses; and processing the received images through a photogrammetry module. The photogrammetry module may provide camera calibration and facilitate camera registration. As such, manual movement or robotic movement capabilities of the camera head, and digital visualization capabilities of a digital surgical microscope disclosed herein can be extended to allow near-automated or fully automated touchless registration for traditional surgical navigation.

Automated touchless registration for surgical navigation

New and innovative systems and methods for calibrating and correcting sensors associated with a collaborative robot are disclosed. An example system comprises: at least one robotic arm; a sensor affixed to a location on the robotic arm, wherein the sensor measures force and torque across six degrees of freedom (6DOF); a processor; and memory. The system may receive, from the sensor, sensor input in real-time that indicate a measured force or torque. The system may generate, in real-time, sensor corrections that correspond to offset, linear, and non-linear deviations of the measured force in each sensor axis. The sensor corrections may correspond to offset, linear, and non-linear cross-coupling of the measured force between two or more sensor axes. The sensor corrections may be determined by applying offset, linear, and non nonlinear corrections to each degree of freedom (DOF) from every other DOF.

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Goleta, CA, United States of America

Michael Larkin