Surgical Robot Error Detection Using Filtered and Raw Tracking 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 to the system or surgical site due to delayed detection.
Innovation Solution
A surgical system comprising a robotic system with a base, a localizer to monitor the tracker, and controllers to determine the relationship between the base and localizer, monitor for errors, and modify the robotic system's operation in response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If low-pass filtering is used to reduce noise levels 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 patent divides the tracking data processing into two separate pathways: a filtered pathway for control commands and an unfiltered pathway for error detection. The low-pass filter is applied only to the control pathway, while the error detection pathway uses raw unfiltered data, allowing error detection without delay while maintaining smooth robot performance through filtering.
Solution Approach 2:
The patent introduces an intermediary error detection mechanism that operates independently from the filtered control loop. By creating a separate error detection pathway that processes unfiltered data, the system can detect errors in real-time without the delays introduced by filtering, while the filtered pathway continues to provide smooth control commands.
2Measurement precision
If tracking system operates at high speed to monitor robot position, then positioning accuracy is improved, but control system stability deteriorates due to noise and bandwidth issues
Solution Approach 1:
The patent segments the high-speed tracking data into two uses: unfiltered data for error detection and filtered data for control commands. This allows the system to maintain high positioning accuracy for error detection while using filtered data for stable control, resolving the contradiction between measurement precision and control stability.
Solution Approach 2:
The patent applies different processing qualities to different data pathways: unfiltered high-precision data is used locally for error detection, while filtered stable data is used locally for control commands. This local quality differentiation allows each pathway to optimize for its specific purpose without compromising the other.
3Stability of the object's composition
If low-pass filter bandwidth is reduced to match robot response capability, then control system stability is improved, but error detection capability deteriorates due to filtering delays
Solution Approach 1:
The patent creates two separate data processing segments: one filtered segment for stable control commands and one unfiltered segment for reliable error detection. This segmentation allows the control system to operate with reduced bandwidth for stability while the error detection system maintains full bandwidth capability for immediate error detection.
Solution Approach 2:
The patent introduces an intermediary unfiltered data pathway that mediates between the filtered control system and the error detection requirement. This intermediary pathway provides real-time error detection capability without being constrained by the bandwidth limitations of the filtered control loop.
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. 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. In response to detection of the error, the controller(s) modify operation of the robotic system.