Surgical Robot Tracking Error Detection With Raw and Filtered Data
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Solution Overview
Problem
Current surgical robotic 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 tracking system errors.
Innovation Solution
A surgical system comprising a robotic system with a localizer, sensors, and controllers that determine and monitor the relationship between the base and localizer to detect errors and identify their cause, utilizing data fusion and filtering techniques to ensure accurate and timely error detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If low-pass filtering is used to reduce noise levels in tracking data, then the signal-to-noise ratio is improved and robot movement becomes smoother, but error detection is delayed because filtering occurs before error detection
Solution Approach 1:
The patent segments the tracking data processing into two separate pathways: a filtered pathway for control commands and a raw pathway for error detection. The raw tracking data is preserved and fed into a separate error detection module that operates independently from the filtering process, allowing simultaneous noise reduction for control and real-time error detection without delay.
Solution Approach 2:
The patent introduces an intermediary raw data buffer that stores unfiltered tracking data specifically for error detection purposes. This intermediary storage allows the system to maintain the filtered data stream for smooth robot control while preserving the original high-frequency tracking data for immediate error analysis, bridging the gap between noise reduction and real-time detection.
2Measurement precision
If tracking system operates at high speed to capture robot positioning, then positioning accuracy is improved, but control system stability deteriorates due to noise and high bandwidth
Solution Approach 1:
The patent divides the high-speed tracking data utilization into two separate functions: one pathway applies low-pass filtering to generate stable control commands at reduced bandwidth, while another pathway preserves the high-frequency raw data for real-time error detection and positioning accuracy monitoring, allowing both stability and precision to coexist through functional separation.
Solution Approach 2:
The patent implements a dual feedback mechanism where filtered tracking data provides feedback for smooth robot control at appropriate bandwidth, while raw unfiltered data provides simultaneous feedback for error detection and system accuracy monitoring, enabling the control system to maintain stability while preserving high-precision positioning information.
Data Source
AI summary
A surgical system and method involve a robotic system with a base and a localizer that monitors a tracker supported by the robotic system. Sensor(s) are coupled to the robotic system and/or the localizer. Controller(s) determine a relationship between the base and the localizer. The controller(s) monitor the relationship to detect an error related to one or both of the robotic system and the localizer. The controller(s) utilize the sensor(s) to determine a cause of the error.