LED Color Sensor Calibration Matrix for Cross-Talk Classification
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Solution Overview
Problem
The challenge in surgical robotic systems is the difficulty in accurately classifying colors from light-emitting diodes (LEDs) due to significant cross-talk between color channels in the color sensor, leading to reduced manufacturing yield and classification accuracy.
Innovation Solution
A method involving a calibration process using a 3x3 matrix to convert RGB color space readings to HSV, applying a calibration matrix to filter out cross-talk, and setting proper thresholds for accurate color classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If color sensors are used to detect LED colors in foot pedals, then visibility and differentiation of pedals is improved, but cross-talk between color channels reduces measurement precision
Solution Approach 1:
The patent applies parameter changes by transforming color measurements from the RGB color space to the HSV color space. This transformation changes the parameters used to represent color, separating hue (color identity) from saturation and value, which helps isolate the cross-talk effect and improve color classification accuracy despite sensor imperfections
Solution Approach 2:
The patent introduces an intermediary calibration matrix that acts as a mediator between the raw sensor measurements and the final color classification. This matrix is derived from measurements of known reference colors and transforms the distorted sensor readings into accurate color space coordinates, effectively compensating for the cross-talk between color channels
2Measurement precision
If strict color classification thresholds are applied, then classification accuracy is improved, but manufacturing yield decreases due to sensor variations
Solution Approach 1:
The patent applies preliminary action by performing calibration measurements during the manufacturing process to characterize each sensor's specific response. This pre-characterization data is stored and used during quality control to set individualized acceptance criteria, allowing sensors with normal variations to pass while still maintaining strict color classification standards
Solution Approach 2:
The patent changes the approach to thresholding by moving from fixed universal thresholds to dynamic thresholds based on each sensor's calibrated response characteristics. This allows the system to accommodate normal manufacturing variations while maintaining accurate color classification, thereby improving manufacturing yield without sacrificing precision
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
Improves manufacturing yield and classification accuracy of LEDs in surgical robotic systems by effectively filtering cross-talk and ensuring precise color reproduction.
Implementation Method 1
The LED lights generate different colors allowing the surgeon to differentiate between foot pedals
Implementation Method 2
measuring a color of the at least one LED in a first color space
Data Source
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AI summary
A method for generating a calibration matrix for light sources includes activating at least one LED of a plurality of multicolor LEDs of a light source and measuring a color of the at least one LED in a first color space. The method also includes scaling the color of the at least one LED relative to the plurality of multicolor LEDs, obtaining a plurality of scaled color measurements, and calculating the calibration matrix based on the plurality of scaled color measurements. A method for calibrating a light source includes activating at least one LED of a plurality of multicolor LEDs of a light source and measuring a color of the at least one LED in a first color space; converting the measured color using a calibration matrix to a calibrated first color space measurement; converting the calibrated first color space measurement to a second color space values; comparing the second color space values to thresholds derived from the calibration matrix; and outputting a calibration failure message in response to the second color space values exceeding the thresholds.