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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
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Calibration Curves: Correlation Coefficient01:10

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In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
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Calibration Curves: Linear Least Squares01:20

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Glassware Calibration01:11

Glassware Calibration

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Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
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Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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Measurement: Standard Units03:38

Measurement: Standard Units

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Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
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Measurement of Spatial Stability in Precision Grip
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Joint Calibration Method for Robot Measurement Systems.

Lei Wu1, Xizhe Zang1, Guanwen Ding1

  • 1State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a joint calibration method for robot measurement systems, significantly improving accuracy. The new approach reduces positioning errors by over 90% for precise workpiece measurement.

Keywords:
Lie algebrabinocular planar structured light camerajoint calibration methodrobot measurement system

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Area of Science:

  • Robotics
  • Metrology
  • Computer Vision

Background:

  • Robot measurement systems using 3D cameras are crucial for workpiece inspection.
  • Measurement accuracy is compromised by robot kinematics, camera installation, and 3D camera errors.
  • Incomplete calibration of these factors leads to significant inaccuracies.

Purpose of the Study:

  • To develop a comprehensive joint calibration method for robot measurement systems.
  • To address and integrate errors from robot kinematics, camera-to-robot installation, and 3D camera measurements.
  • To enhance overall measurement accuracy in robotic inspection applications.

Main Methods:

  • Formulated robot kinematics and camera-to-robot installation error models using Lie algebra.
  • Developed a novel pillow error model for the 3D camera.
  • Constructed a joint error model using homogeneous transformation and solved via stepwise optimization.

Main Results:

  • Significantly improved measurement accuracy was demonstrated through simulations and experiments.
  • Reduced mean positioning error from over 2.5228 mm to 0.2629 mm.
  • Reduced mean distance error from over 0.1488 mm to 0.1232 mm.

Conclusions:

  • The proposed joint calibration method effectively enhances the accuracy of robot measurement systems.
  • The integration of Lie algebra and a pillow error model provides a robust solution.
  • This approach offers a substantial improvement for precise workpiece shape and position measurement.