Surgical Robot Registration via Simultaneous Point Cloud Acquisition
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Solution Overview
Problem
Current robotic-assisted surgery registration methods require multiple steps and additional equipment, increasing operation time and risk of collision, while also being prone to human error and lacking precision due to the need for separate frame of reference matching between surgical robots and optical navigators.
Innovation Solution
A simplified registration method combining the first and second registration steps using an optical distance sensor and optical acquisition means, eliminating the need for additional equipment and manual intervention by directly utilizing data from the robot-patient registration, allowing for simultaneous point cloud acquisition and automatic calculation of transfer matrices between frames of reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple separate registration steps are performed between surgical robot and optical navigator, then frame of reference matching can be achieved, but operation time increases and risk of collision increases
Solution Approach 1:
The patent combines the first registration (between surgical robot and patient) and second registration (between optical navigator and patient) into a single simultaneous registration process. Both the surgical robot and optical navigator acquire point clouds of the patient's anatomical surface at the same time, and the processing unit calculates all transfer matrices (robot-to-patient, navigator-to-patient, and robot-to-navigator) in one unified computation, eliminating the need for sequential registration steps and reducing operation time.
Solution Approach 2:
The patent performs preliminary acquisition of point clouds by both the surgical robot and optical navigator simultaneously before any registration calculations are performed. This preliminary data collection ensures that all necessary spatial information is available upfront, allowing the processing unit to compute all required transfer matrices in a single operation without requiring subsequent registration steps.
2Measurement precision
If additional equipment is used for registration, then frame of reference matching can be achieved, but device complexity increases
Solution Approach 1:
The patent makes the surgical robot and optical navigator multi-functional by enabling them to perform both their primary functions and registration functions simultaneously. The surgical robot's detection unit and the optical navigator's detection unit both serve as point cloud acquisition devices for registration purposes, eliminating the need for separate registration equipment and reducing overall device complexity.
Solution Approach 2:
The surgical robot and optical navigator perform their own registration data collection independently using their existing detection units, without requiring external registration equipment. The processing unit then integrates these self-collected data sets to calculate the necessary transfer matrices, allowing the system to register itself without additional specialized registration tools.
3Measurement precision
If manual intervention is required for registration, then frame of reference matching can be achieved, but human error increases and precision decreases
Solution Approach 1:
The patent implements an automated feedback loop where the processing unit receives point cloud data from both the surgical robot and optical navigator, automatically calculates the transfer matrices using coordinate transformation algorithms, and updates the frame of reference mappings without human intervention. This automated feedback process eliminates manual registration operations and the associated human errors.
Solution Approach 2:
The patent replaces manual mechanical registration operations with automated computational processing. Instead of requiring operators to manually manipulate equipment or input data, the system uses detection units to automatically acquire point clouds and employs processing units to compute transfer matrices through algorithmic coordinate transformations, substituting mechanical/manual operations with automated information processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces operation time, eliminates equipment manipulation, and enhances precision and reproducibility by directly using shared data for registration between surgical robots and optical navigators, ensuring accurate alignment of frames of reference without additional steps or equipment.
Implementation Method 1
detection means forming a first three-dimensional location system comprising an optical distance sensor
Implementation Method 2
at least one means for the acquisition of optical signals in the form of light points projected onto a surface
Data Source
AI summary
This invention concerns an automated registration method and device for a surgical robot enabling registration between a first three-dimensional location system comprising an optical distance sensor and a second three-dimensional location system comprising optical acquisition means. The method comprises:a first step of intraoperative registration between the first location system and data recorded on an anatomical surface of a patient and;a second step of intraoperative registration of two three-dimensional location systems.The second registration step is performed at the same time as the first registration step by detection, by the optical acquisition means, of at least one point of a point cloud acquired by the optical sensor during the first intraoperative registration.