Surgical Robot Tracking Architecture for Real-Time Error Detection
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Solution Overview
Problem
Current robotic surgical systems are unable to detect errors or loss of accuracy in real time, leading to potential damage during surgical procedures due to delayed detection of positioning errors caused by noise and control system stability issues in high-speed tracking data.
Innovation Solution
A robotic surgical system comprising a manipulator, a navigation system, and controllers that determine the relationship between components using kinematic measurement data and navigation data to detect errors such as undesired movement, component failures, or improper calibration, allowing for immediate error detection and prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If low-pass filtering is applied to tracking data to reduce noise and improve signal-to-noise ratio, then the robot movement becomes smoother and performance improves, but error detection is delayed due to filtering delays
Solution Approach 1:
The system segments the tracking data processing into two independent pathways: a filtered pathway for control commands and an unfiltered pathway for error detection. The unfiltered pathway processes raw tracking data through a separate transform model to detect errors in real-time without the delays introduced by low-pass filtering in the control pathway.
Solution Approach 2:
A separate unfiltered transform model acts as an intermediary for error detection. This intermediary pathway processes raw tracking data without applying the low-pass filter, allowing error detection to occur in real-time while the filtered pathway continues to provide smooth control commands to the robot.
2Productivity
If tracking system operates at high speed to capture robot positioning, then positioning data is captured more frequently, but noise levels increase and control system stability is compromised
Solution Approach 1:
The system divides the high-speed tracking data processing into two separate streams: one stream applies low-pass filtering to ensure control system stability, while the other stream processes unfiltered data for real-time error detection. This segmentation allows the system to maintain both stability and high tracking speed.
Solution Approach 2:
Different quality processing is applied to different portions of the tracking data: the control pathway receives filtered, smoothed data for stability, while the error detection pathway receives raw, unfiltered data for accurate real-time monitoring. Each pathway receives the appropriate data quality for its specific function.
Data Source
AI summary
Systems and methods for operating a robotic surgical system are provided. The system includes a surgical tool, a manipulator comprising links for controlling the tool, a navigation system includes a tracker and a localizer to monitor a state of the tracker. Controller(s) determine a relationship between one or more components of the manipulator and one or more components of the navigation system by utilizing kinematic measurement data from the manipulator and navigation data from the navigation system. The controller(s) utilize the relationship to determine whether an error has occurred relating to at least one of the manipulator and the navigation system. The error is at least one of undesired movement of the manipulator, undesired movement of the localizer, failure of any one or more components of the manipulator or the localizer, and/or improper calibration data.