MAKO Surgical robotic arm deflection estimation using machine learning
Summary
MAKO Surgical Corp. published patent application US20260090848A1 on April 2, 2026, describing machine learning techniques for estimating deflection of surgical robotic arms. The invention uses tool pose and interaction force inputs to train models that predict arm deflection and characterize tool-anatomy interactions during surgical procedures.
What changed
The published patent application describes a surgical system where controllers input the pose of a surgical tool and tool interaction force into a machine learning model to estimate robotic arm deflection. A second model characterizes tool-anatomy interaction by processing operating parameters of the surgical tool alongside the estimated deflection. The system uses CPC classifications A61B 34/30, A61B 90/06, and A61B 2034/305.
Patent applications do not impose compliance obligations or deadlines on regulated entities. Healthcare providers and medical device manufacturers reviewing this publication should be aware that it represents published prior art and may inform intellectual property strategy around surgical robotics and machine learning integration in medical procedures.
Archived snapshot
Apr 2, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Techniques For Estimating Deflection Of A Surgical Robotic Arm
Application US20260090848A1 Kind: A1 Apr 02, 2026
Assignee
MAKO Surgical Corp.
Inventors
Ali Talasaz
Abstract
Surgical systems and methods involve a robotic arm comprising a plurality of links and joints and a surgical tool supported and moveable by the robotic arm and being configured to interact with an anatomy. Controller(s) coupled to the robotic arm are configured to estimate robotic arm deflection based on the tool interaction and/or characterize tool-anatomy interaction based on estimated arm deflection. To estimate the robotic arm deflection, the controller(s) input the pose of the surgical tool and the tool interaction force to a machine learning model. To characterize the interaction of the surgical tool with the anatomy, the controllers(s) input an operating parameter of the surgical tool and the estimated deflection into a machine learning model.
CPC Classifications
A61B 34/30 A61B 90/06 A61B 2034/305 A61B 2090/064
Filing Date
2025-09-25
Application No.
19339378
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